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"e92c33ea498915a13c9aec162616db18", + "translation_date": "2025-08-24T22:13:19+00:00", + "source_file": "quiz-app/README.md", + "language_code": "hi" + }, + "sketchnotes/README.md": { + "original_hash": "3a848466cb63aff1a93411affb152c2a", + "translation_date": "2025-08-24T21:45:19+00:00", + "source_file": "sketchnotes/README.md", + "language_code": "hi" + } +} \ No newline at end of file diff --git a/translations/hi/1-Introduction/01-defining-data-science/README.md b/translations/hi/1-Introduction/01-defining-data-science/README.md index 8d2cdbba..49058a85 100644 --- a/translations/hi/1-Introduction/01-defining-data-science/README.md +++ b/translations/hi/1-Introduction/01-defining-data-science/README.md @@ -1,12 +1,3 @@ - # डेटा साइंस की परिभाषा | ![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/01-Definitions.png) | diff --git a/translations/hi/1-Introduction/01-defining-data-science/assignment.md b/translations/hi/1-Introduction/01-defining-data-science/assignment.md index 83967835..26a7901e 100644 --- a/translations/hi/1-Introduction/01-defining-data-science/assignment.md +++ b/translations/hi/1-Introduction/01-defining-data-science/assignment.md @@ -1,12 +1,3 @@ - # असाइनमेंट: डेटा साइंस परिदृश्य इस पहले असाइनमेंट में, हम आपसे यह सोचने के लिए कहते हैं कि विभिन्न समस्या क्षेत्रों में किसी वास्तविक जीवन की प्रक्रिया या समस्या को कैसे बेहतर बनाया जा सकता है, और इसे डेटा साइंस प्रक्रिया का उपयोग करके कैसे सुधार सकते हैं। निम्नलिखित पर विचार करें: diff --git a/translations/hi/1-Introduction/01-defining-data-science/solution/assignment.md b/translations/hi/1-Introduction/01-defining-data-science/solution/assignment.md index c6b50816..ce250d63 100644 --- a/translations/hi/1-Introduction/01-defining-data-science/solution/assignment.md +++ b/translations/hi/1-Introduction/01-defining-data-science/solution/assignment.md @@ -1,12 +1,3 @@ - # असाइनमेंट: डेटा साइंस परिदृश्य इस पहले असाइनमेंट में, हम आपसे यह सोचने के लिए कहते हैं कि वास्तविक जीवन की किसी प्रक्रिया या समस्या को विभिन्न समस्या क्षेत्रों में कैसे बेहतर बनाया जा सकता है, और डेटा साइंस प्रक्रिया का उपयोग करके इसे कैसे सुधार सकते हैं। निम्नलिखित पर विचार करें: diff --git a/translations/hi/1-Introduction/02-ethics/README.md b/translations/hi/1-Introduction/02-ethics/README.md index 14717ac2..35de530e 100644 --- a/translations/hi/1-Introduction/02-ethics/README.md +++ b/translations/hi/1-Introduction/02-ethics/README.md @@ -1,12 +1,3 @@ - # डेटा नैतिकता का परिचय |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/02-Ethics.png)| diff --git a/translations/hi/1-Introduction/02-ethics/assignment.md b/translations/hi/1-Introduction/02-ethics/assignment.md index d8594fea..15d84095 100644 --- a/translations/hi/1-Introduction/02-ethics/assignment.md +++ b/translations/hi/1-Introduction/02-ethics/assignment.md @@ -1,12 +1,3 @@ - ## डेटा एथिक्स केस स्टडी लिखें ## निर्देश diff --git a/translations/hi/1-Introduction/03-defining-data/README.md b/translations/hi/1-Introduction/03-defining-data/README.md index e2ad8bec..fbab976c 100644 --- a/translations/hi/1-Introduction/03-defining-data/README.md +++ b/translations/hi/1-Introduction/03-defining-data/README.md @@ -1,12 +1,3 @@ - # डेटा को परिभाषित करना |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/03-DefiningData.png)| diff --git a/translations/hi/1-Introduction/03-defining-data/assignment.md b/translations/hi/1-Introduction/03-defining-data/assignment.md index fbdded4e..de1f4ca0 100644 --- a/translations/hi/1-Introduction/03-defining-data/assignment.md +++ b/translations/hi/1-Introduction/03-defining-data/assignment.md @@ -1,12 +1,3 @@ - # डेटा सेट वर्गीकृत करना ## निर्देश diff --git a/translations/hi/1-Introduction/04-stats-and-probability/README.md b/translations/hi/1-Introduction/04-stats-and-probability/README.md index f08ed51a..a49a7ad5 100644 --- a/translations/hi/1-Introduction/04-stats-and-probability/README.md +++ b/translations/hi/1-Introduction/04-stats-and-probability/README.md @@ -1,12 +1,3 @@ - # सांख्यिकी और संभाव्यता का संक्षिप्त परिचय |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/04-Statistics-Probability.png)| @@ -64,7 +55,7 @@ CO_OP_TRANSLATOR_METADATA: ग्राफ़िक रूप से हम माध्यिका और क्वारटाइल्स के बीच संबंध को **बॉक्स प्लॉट** नामक आरेख में प्रस्तुत कर सकते हैं: -बॉक्स प्लॉट व्याख्या +बॉक्स प्लॉट व्याख्या यहां हम **इंटर-क्वारटाइल रेंज** IQR=Q3-Q1 और तथाकथित **आउटलायर्स** - मान जो [Q1-1.5*IQR,Q3+1.5*IQR] की सीमाओं के बाहर होते हैं, की भी गणना करते हैं। diff --git a/translations/hi/1-Introduction/04-stats-and-probability/assignment.md b/translations/hi/1-Introduction/04-stats-and-probability/assignment.md index e75d80e7..f3e2b822 100644 --- a/translations/hi/1-Introduction/04-stats-and-probability/assignment.md +++ b/translations/hi/1-Introduction/04-stats-and-probability/assignment.md @@ -1,12 +1,3 @@ - # छोटे डायबिटीज अध्ययन इस असाइनमेंट में, हम डायबिटीज मरीजों के एक छोटे डेटा सेट के साथ काम करेंगे, जो [यहां](https://www4.stat.ncsu.edu/~boos/var.select/diabetes.html) से लिया गया है। diff --git a/translations/hi/1-Introduction/README.md b/translations/hi/1-Introduction/README.md index aa08c5b0..4e43cc61 100644 --- a/translations/hi/1-Introduction/README.md +++ b/translations/hi/1-Introduction/README.md @@ -1,12 +1,3 @@ - # डेटा साइंस का परिचय ![डेटा इन एक्शन](../../../translated_images/hi/data.48e22bb7617d8d92188afbc4c48effb920ba79f5cebdc0652cd9f34bbbd90c18.jpg) diff --git a/translations/hi/2-Working-With-Data/05-relational-databases/README.md b/translations/hi/2-Working-With-Data/05-relational-databases/README.md index afc2e516..5a045a13 100644 --- a/translations/hi/2-Working-With-Data/05-relational-databases/README.md +++ b/translations/hi/2-Working-With-Data/05-relational-databases/README.md @@ -1,12 +1,3 @@ - # डेटा के साथ काम करना: रिलेशनल डेटाबेस |![ स्केचनोट द्वारा [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/05-RelationalData.png)| diff --git a/translations/hi/2-Working-With-Data/05-relational-databases/assignment.md b/translations/hi/2-Working-With-Data/05-relational-databases/assignment.md index 3b60fcc8..741c348b 100644 --- a/translations/hi/2-Working-With-Data/05-relational-databases/assignment.md +++ b/translations/hi/2-Working-With-Data/05-relational-databases/assignment.md @@ -1,12 +1,3 @@ - # हवाई अड्डे का डेटा प्रदर्शित करना आपको [SQLite](https://sqlite.org/index.html) पर आधारित एक [डेटाबेस](https://raw.githubusercontent.com/Microsoft/Data-Science-For-Beginners/main/2-Working-With-Data/05-relational-databases/airports.db) प्रदान किया गया है, जिसमें हवाई अड्डों की जानकारी है। नीचे स्कीमा प्रदर्शित किया गया है। आप [Visual Studio Code](https://code.visualstudio.com?WT.mc_id=academic-77958-bethanycheum) में [SQLite एक्सटेंशन](https://marketplace.visualstudio.com/items?itemName=alexcvzz.vscode-sqlite&WT.mc_id=academic-77958-bethanycheum) का उपयोग करके विभिन्न शहरों के हवाई अड्डों की जानकारी प्रदर्शित करेंगे। diff --git a/translations/hi/2-Working-With-Data/06-non-relational/README.md b/translations/hi/2-Working-With-Data/06-non-relational/README.md index 01440be9..bf8d33f2 100644 --- a/translations/hi/2-Working-With-Data/06-non-relational/README.md +++ b/translations/hi/2-Working-With-Data/06-non-relational/README.md @@ -1,12 +1,3 @@ - # डेटा के साथ काम करना: गैर-संबंधात्मक डेटा |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/06-NoSQL.png)| diff --git a/translations/hi/2-Working-With-Data/06-non-relational/assignment.md b/translations/hi/2-Working-With-Data/06-non-relational/assignment.md index 5464a3f7..f31365ea 100644 --- a/translations/hi/2-Working-With-Data/06-non-relational/assignment.md +++ b/translations/hi/2-Working-With-Data/06-non-relational/assignment.md @@ -1,12 +1,3 @@ - # सोडा मुनाफा ## निर्देश diff --git a/translations/hi/2-Working-With-Data/07-python/README.md b/translations/hi/2-Working-With-Data/07-python/README.md index b5aab07e..e7125161 100644 --- a/translations/hi/2-Working-With-Data/07-python/README.md +++ b/translations/hi/2-Working-With-Data/07-python/README.md @@ -1,12 +1,3 @@ - # डेटा के साथ काम करना: Python और Pandas लाइब्रेरी | ![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/07-WorkWithPython.png) | diff --git a/translations/hi/2-Working-With-Data/07-python/assignment.md b/translations/hi/2-Working-With-Data/07-python/assignment.md index 01adf71c..e0259db1 100644 --- a/translations/hi/2-Working-With-Data/07-python/assignment.md +++ b/translations/hi/2-Working-With-Data/07-python/assignment.md @@ -1,12 +1,3 @@ - # पायथन में डेटा प्रोसेसिंग के लिए असाइनमेंट इस असाइनमेंट में, हम आपसे उन कोड्स को विस्तार से समझाने के लिए कहेंगे, जिन्हें हमने अपने चैलेंजेस में विकसित करना शुरू किया है। असाइनमेंट दो भागों में विभाजित है: diff --git a/translations/hi/2-Working-With-Data/08-data-preparation/README.md b/translations/hi/2-Working-With-Data/08-data-preparation/README.md index 73a7d8cc..11a6d81b 100644 --- a/translations/hi/2-Working-With-Data/08-data-preparation/README.md +++ b/translations/hi/2-Working-With-Data/08-data-preparation/README.md @@ -1,12 +1,3 @@ - # डेटा के साथ काम करना: डेटा तैयारी |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/08-DataPreparation.png)| diff --git a/translations/hi/2-Working-With-Data/08-data-preparation/assignment.md b/translations/hi/2-Working-With-Data/08-data-preparation/assignment.md index 143561f6..7886e73f 100644 --- a/translations/hi/2-Working-With-Data/08-data-preparation/assignment.md +++ b/translations/hi/2-Working-With-Data/08-data-preparation/assignment.md @@ -1,12 +1,3 @@ - # फॉर्म से डेटा का मूल्यांकन एक क्लाइंट ने अपने ग्राहक आधार के बारे में कुछ बुनियादी डेटा इकट्ठा करने के लिए [छोटा फॉर्म](../../../../2-Working-With-Data/08-data-preparation/index.html) का परीक्षण किया है। उन्होंने अपने निष्कर्ष आपके पास लाए हैं ताकि आप उनके द्वारा इकट्ठा किए गए डेटा को मान्य कर सकें। आप ब्राउज़र में `index.html` पेज खोलकर फॉर्म देख सकते हैं। diff --git a/translations/hi/2-Working-With-Data/README.md b/translations/hi/2-Working-With-Data/README.md index ae95cabc..764638a1 100644 --- a/translations/hi/2-Working-With-Data/README.md +++ b/translations/hi/2-Working-With-Data/README.md @@ -1,12 +1,3 @@ - # डेटा के साथ काम करना ![data love](../../../translated_images/hi/data-love.a22ef29e6742c852505ada062920956d3d7604870b281a8ca7c7ac6f37381d5a.jpg) diff --git a/translations/hi/3-Data-Visualization/09-visualization-quantities/README.md b/translations/hi/3-Data-Visualization/09-visualization-quantities/README.md index ecc7163e..0c902ebd 100644 --- a/translations/hi/3-Data-Visualization/09-visualization-quantities/README.md +++ b/translations/hi/3-Data-Visualization/09-visualization-quantities/README.md @@ -1,12 +1,3 @@ - # मात्राओं का विज़ुअलाइज़ेशन |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/09-Visualizing-Quantities.png)| diff --git a/translations/hi/3-Data-Visualization/09-visualization-quantities/assignment.md b/translations/hi/3-Data-Visualization/09-visualization-quantities/assignment.md index 959ca77b..1f277630 100644 --- a/translations/hi/3-Data-Visualization/09-visualization-quantities/assignment.md +++ b/translations/hi/3-Data-Visualization/09-visualization-quantities/assignment.md @@ -1,12 +1,3 @@ - # रेखाएं, बिखराव और बार ## निर्देश diff --git a/translations/hi/3-Data-Visualization/10-visualization-distributions/README.md b/translations/hi/3-Data-Visualization/10-visualization-distributions/README.md index 2e75bc32..eb1a8e4a 100644 --- a/translations/hi/3-Data-Visualization/10-visualization-distributions/README.md +++ b/translations/hi/3-Data-Visualization/10-visualization-distributions/README.md @@ -1,12 +1,3 @@ - # वितरणों का विज़ुअलाइज़ेशन |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/10-Visualizing-Distributions.png)| diff --git a/translations/hi/3-Data-Visualization/10-visualization-distributions/assignment.md b/translations/hi/3-Data-Visualization/10-visualization-distributions/assignment.md index 0dc3d9b9..4bf5e27f 100644 --- a/translations/hi/3-Data-Visualization/10-visualization-distributions/assignment.md +++ b/translations/hi/3-Data-Visualization/10-visualization-distributions/assignment.md @@ -1,12 +1,3 @@ - # अपने कौशल का उपयोग करें ## निर्देश diff --git a/translations/hi/3-Data-Visualization/11-visualization-proportions/README.md b/translations/hi/3-Data-Visualization/11-visualization-proportions/README.md index a5ce1a3e..5cbece1e 100644 --- a/translations/hi/3-Data-Visualization/11-visualization-proportions/README.md +++ b/translations/hi/3-Data-Visualization/11-visualization-proportions/README.md @@ -1,12 +1,3 @@ - # अनुपातों का दृश्यांकन |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/11-Visualizing-Proportions.png)| diff --git a/translations/hi/3-Data-Visualization/11-visualization-proportions/assignment.md b/translations/hi/3-Data-Visualization/11-visualization-proportions/assignment.md index 1fb3b31f..e3a6b07f 100644 --- a/translations/hi/3-Data-Visualization/11-visualization-proportions/assignment.md +++ b/translations/hi/3-Data-Visualization/11-visualization-proportions/assignment.md @@ -1,12 +1,3 @@ - # इसे Excel में आज़माएं ## निर्देश diff --git a/translations/hi/3-Data-Visualization/12-visualization-relationships/README.md b/translations/hi/3-Data-Visualization/12-visualization-relationships/README.md index 0b5b3202..a89bbf0f 100644 --- a/translations/hi/3-Data-Visualization/12-visualization-relationships/README.md +++ b/translations/hi/3-Data-Visualization/12-visualization-relationships/README.md @@ -1,12 +1,3 @@ - # संबंधों का चित्रण: शहद के बारे में सब कुछ 🍯 |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/12-Visualizing-Relationships.png)| diff --git a/translations/hi/3-Data-Visualization/12-visualization-relationships/assignment.md b/translations/hi/3-Data-Visualization/12-visualization-relationships/assignment.md index 3d83dd94..dd66975b 100644 --- a/translations/hi/3-Data-Visualization/12-visualization-relationships/assignment.md +++ b/translations/hi/3-Data-Visualization/12-visualization-relationships/assignment.md @@ -1,12 +1,3 @@ - # मधुमक्खी के छत्ते में गोता लगाएं ## निर्देश diff --git a/translations/hi/3-Data-Visualization/13-meaningful-visualizations/README.md b/translations/hi/3-Data-Visualization/13-meaningful-visualizations/README.md index eff7d422..06a4a588 100644 --- a/translations/hi/3-Data-Visualization/13-meaningful-visualizations/README.md +++ b/translations/hi/3-Data-Visualization/13-meaningful-visualizations/README.md @@ -1,12 +1,3 @@ - # सार्थक डेटा विज़ुअलाइज़ेशन बनाना |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/13-MeaningfulViz.png)| diff --git a/translations/hi/3-Data-Visualization/13-meaningful-visualizations/assignment.md b/translations/hi/3-Data-Visualization/13-meaningful-visualizations/assignment.md index 9702a45d..989b9947 100644 --- a/translations/hi/3-Data-Visualization/13-meaningful-visualizations/assignment.md +++ b/translations/hi/3-Data-Visualization/13-meaningful-visualizations/assignment.md @@ -1,12 +1,3 @@ - # अपना खुद का कस्टम विज़ुअलाइज़ेशन बनाएं ## निर्देश diff --git a/translations/hi/3-Data-Visualization/13-meaningful-visualizations/solution/README.md b/translations/hi/3-Data-Visualization/13-meaningful-visualizations/solution/README.md index 0f27755f..e2ed83f1 100644 --- a/translations/hi/3-Data-Visualization/13-meaningful-visualizations/solution/README.md +++ b/translations/hi/3-Data-Visualization/13-meaningful-visualizations/solution/README.md @@ -1,12 +1,3 @@ - # डेंजरस लिआज़ॉन्स डेटा विज़ुअलाइज़ेशन प्रोजेक्ट शुरू करने के लिए, सुनिश्चित करें कि आपके सिस्टम पर NPM और Node चल रहे हैं। डिपेंडेंसीज़ इंस्टॉल करें (npm install) और फिर प्रोजेक्ट को लोकली चलाएं (npm run serve): diff --git a/translations/hi/3-Data-Visualization/13-meaningful-visualizations/starter/README.md b/translations/hi/3-Data-Visualization/13-meaningful-visualizations/starter/README.md index 6d7b659f..ab1d6de3 100644 --- a/translations/hi/3-Data-Visualization/13-meaningful-visualizations/starter/README.md +++ b/translations/hi/3-Data-Visualization/13-meaningful-visualizations/starter/README.md @@ -1,12 +1,3 @@ - # डेंजरस लिआज़ॉन्स डेटा विज़ुअलाइज़ेशन प्रोजेक्ट शुरू करने के लिए, सुनिश्चित करें कि आपके सिस्टम पर NPM और Node चल रहे हैं। डिपेंडेंसीज़ इंस्टॉल करें (npm install) और फिर प्रोजेक्ट को लोकल रूप से चलाएं (npm run serve): diff --git a/translations/hi/3-Data-Visualization/R/09-visualization-quantities/README.md b/translations/hi/3-Data-Visualization/R/09-visualization-quantities/README.md index 25a5e429..01d7045c 100644 --- a/translations/hi/3-Data-Visualization/R/09-visualization-quantities/README.md +++ b/translations/hi/3-Data-Visualization/R/09-visualization-quantities/README.md @@ -1,12 +1,3 @@ - # मात्राओं का विज़ुअलाइज़ेशन |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/sketchnotes/09-Visualizing-Quantities.png)| |:---:| diff --git a/translations/hi/3-Data-Visualization/R/09-visualization-quantities/assignment.md b/translations/hi/3-Data-Visualization/R/09-visualization-quantities/assignment.md index 10de6bf6..f342581b 100644 --- a/translations/hi/3-Data-Visualization/R/09-visualization-quantities/assignment.md +++ b/translations/hi/3-Data-Visualization/R/09-visualization-quantities/assignment.md @@ -1,12 +1,3 @@ - # रेखाएं, बिखराव और बार्स ## निर्देश diff --git a/translations/hi/3-Data-Visualization/R/10-visualization-distributions/README.md b/translations/hi/3-Data-Visualization/R/10-visualization-distributions/README.md index 832a6dd1..0a2572f6 100644 --- a/translations/hi/3-Data-Visualization/R/10-visualization-distributions/README.md +++ b/translations/hi/3-Data-Visualization/R/10-visualization-distributions/README.md @@ -1,12 +1,3 @@ - # वितरणों का विज़ुअलाइज़ेशन |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/sketchnotes/10-Visualizing-Distributions.png)| diff --git a/translations/hi/3-Data-Visualization/R/10-visualization-distributions/assignment.md b/translations/hi/3-Data-Visualization/R/10-visualization-distributions/assignment.md index 69d743ac..292804ca 100644 --- a/translations/hi/3-Data-Visualization/R/10-visualization-distributions/assignment.md +++ b/translations/hi/3-Data-Visualization/R/10-visualization-distributions/assignment.md @@ -1,12 +1,3 @@ - # अपने कौशल का उपयोग करें ## निर्देश diff --git a/translations/hi/3-Data-Visualization/R/11-visualization-proportions/README.md b/translations/hi/3-Data-Visualization/R/11-visualization-proportions/README.md index 27aa6766..969aebbc 100644 --- a/translations/hi/3-Data-Visualization/R/11-visualization-proportions/README.md +++ b/translations/hi/3-Data-Visualization/R/11-visualization-proportions/README.md @@ -1,12 +1,3 @@ - # अनुपातों का विज़ुअलाइज़ेशन |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../../sketchnotes/11-Visualizing-Proportions.png)| diff --git a/translations/hi/3-Data-Visualization/R/12-visualization-relationships/README.md b/translations/hi/3-Data-Visualization/R/12-visualization-relationships/README.md index 77e2a6e2..b84a0e5b 100644 --- a/translations/hi/3-Data-Visualization/R/12-visualization-relationships/README.md +++ b/translations/hi/3-Data-Visualization/R/12-visualization-relationships/README.md @@ -1,12 +1,3 @@ - # संबंधों का चित्रण: शहद के बारे में सब कुछ 🍯 |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../../sketchnotes/12-Visualizing-Relationships.png)| diff --git a/translations/hi/3-Data-Visualization/R/13-meaningful-vizualizations/README.md b/translations/hi/3-Data-Visualization/R/13-meaningful-vizualizations/README.md index 70a1418a..19d43f6d 100644 --- a/translations/hi/3-Data-Visualization/R/13-meaningful-vizualizations/README.md +++ b/translations/hi/3-Data-Visualization/R/13-meaningful-vizualizations/README.md @@ -1,12 +1,3 @@ - # सार्थक विज़ुअलाइज़ेशन बनाना |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../../sketchnotes/13-MeaningfulViz.png)| diff --git a/translations/hi/3-Data-Visualization/README.md b/translations/hi/3-Data-Visualization/README.md index f6c64204..e6c89118 100644 --- a/translations/hi/3-Data-Visualization/README.md +++ b/translations/hi/3-Data-Visualization/README.md @@ -1,12 +1,3 @@ - # विज़ुअलाइज़ेशन ![लैवेंडर फूल पर एक मधुमक्खी](../../../translated_images/hi/bee.0aa1d91132b12e3a8994b9ca12816d05ce1642010d9b8be37f8d37365ba845cf.jpg) diff --git a/translations/hi/4-Data-Science-Lifecycle/14-Introduction/README.md b/translations/hi/4-Data-Science-Lifecycle/14-Introduction/README.md index 06430696..f4df9a07 100644 --- a/translations/hi/4-Data-Science-Lifecycle/14-Introduction/README.md +++ b/translations/hi/4-Data-Science-Lifecycle/14-Introduction/README.md @@ -1,12 +1,3 @@ - # डेटा साइंस जीवनचक्र का परिचय |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/14-DataScience-Lifecycle.png)| diff --git a/translations/hi/4-Data-Science-Lifecycle/14-Introduction/assignment.md b/translations/hi/4-Data-Science-Lifecycle/14-Introduction/assignment.md index e950a631..00d0b133 100644 --- a/translations/hi/4-Data-Science-Lifecycle/14-Introduction/assignment.md +++ b/translations/hi/4-Data-Science-Lifecycle/14-Introduction/assignment.md @@ -1,12 +1,3 @@ - # डेटासेट का मूल्यांकन एक क्लाइंट ने आपकी टीम से न्यूयॉर्क सिटी में टैक्सी ग्राहकों की मौसमी खर्च करने की आदतों की जांच में मदद मांगी है। diff --git a/translations/hi/4-Data-Science-Lifecycle/15-analyzing/README.md b/translations/hi/4-Data-Science-Lifecycle/15-analyzing/README.md index 98c36995..7491fcb4 100644 --- a/translations/hi/4-Data-Science-Lifecycle/15-analyzing/README.md +++ b/translations/hi/4-Data-Science-Lifecycle/15-analyzing/README.md @@ -1,12 +1,3 @@ - # डेटा साइंस जीवनचक्र: विश्लेषण |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/15-Analyzing.png)| diff --git a/translations/hi/4-Data-Science-Lifecycle/15-analyzing/assignment.md b/translations/hi/4-Data-Science-Lifecycle/15-analyzing/assignment.md index 4dd24112..5f624a9b 100644 --- a/translations/hi/4-Data-Science-Lifecycle/15-analyzing/assignment.md +++ b/translations/hi/4-Data-Science-Lifecycle/15-analyzing/assignment.md @@ -1,12 +1,3 @@ - # उत्तरों की खोज यह पिछले पाठ के [असाइनमेंट](../14-Introduction/assignment.md) का विस्तार है, जहां हमने डेटा सेट पर एक संक्षिप्त नज़र डाली थी। अब हम डेटा को और गहराई से समझने की कोशिश करेंगे। diff --git a/translations/hi/4-Data-Science-Lifecycle/16-communication/README.md b/translations/hi/4-Data-Science-Lifecycle/16-communication/README.md index a58019ae..a6c15a96 100644 --- a/translations/hi/4-Data-Science-Lifecycle/16-communication/README.md +++ b/translations/hi/4-Data-Science-Lifecycle/16-communication/README.md @@ -1,12 +1,3 @@ - # डेटा साइंस जीवनचक्र: संचार |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा](../../sketchnotes/16-Communicating.png)| diff --git a/translations/hi/4-Data-Science-Lifecycle/16-communication/assignment.md b/translations/hi/4-Data-Science-Lifecycle/16-communication/assignment.md index 245a1ce3..298747ca 100644 --- a/translations/hi/4-Data-Science-Lifecycle/16-communication/assignment.md +++ b/translations/hi/4-Data-Science-Lifecycle/16-communication/assignment.md @@ -1,12 +1,3 @@ - # एक कहानी सुनाएं ## निर्देश diff --git a/translations/hi/4-Data-Science-Lifecycle/README.md b/translations/hi/4-Data-Science-Lifecycle/README.md index 74b86677..9c75a259 100644 --- a/translations/hi/4-Data-Science-Lifecycle/README.md +++ b/translations/hi/4-Data-Science-Lifecycle/README.md @@ -1,12 +1,3 @@ - # डेटा साइंस जीवनचक्र ![communication](../../../translated_images/hi/communication.06d8e2a88d30d168d661ad9f9f0a4f947ebff3719719cfdaf9ed00a406a01ead.jpg) diff --git a/translations/hi/5-Data-Science-In-Cloud/17-Introduction/README.md b/translations/hi/5-Data-Science-In-Cloud/17-Introduction/README.md index 23bae8c0..44f2ea05 100644 --- a/translations/hi/5-Data-Science-In-Cloud/17-Introduction/README.md +++ b/translations/hi/5-Data-Science-In-Cloud/17-Introduction/README.md @@ -1,12 +1,3 @@ - # क्लाउड में डेटा साइंस का परिचय |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/17-DataScience-Cloud.png)| diff --git a/translations/hi/5-Data-Science-In-Cloud/17-Introduction/assignment.md b/translations/hi/5-Data-Science-In-Cloud/17-Introduction/assignment.md index 2ea8154f..9a21b7f2 100644 --- a/translations/hi/5-Data-Science-In-Cloud/17-Introduction/assignment.md +++ b/translations/hi/5-Data-Science-In-Cloud/17-Introduction/assignment.md @@ -1,12 +1,3 @@ - # बाजार अनुसंधान ## निर्देश diff --git a/translations/hi/5-Data-Science-In-Cloud/18-Low-Code/README.md b/translations/hi/5-Data-Science-In-Cloud/18-Low-Code/README.md index cc95d749..2a636cf1 100644 --- a/translations/hi/5-Data-Science-In-Cloud/18-Low-Code/README.md +++ b/translations/hi/5-Data-Science-In-Cloud/18-Low-Code/README.md @@ -1,12 +1,3 @@ - # क्लाउड में डेटा साइंस: "लो कोड/नो कोड" तरीका |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/18-DataScience-Cloud.png)| diff --git a/translations/hi/5-Data-Science-In-Cloud/18-Low-Code/assignment.md b/translations/hi/5-Data-Science-In-Cloud/18-Low-Code/assignment.md index 120bf1f4..59192707 100644 --- a/translations/hi/5-Data-Science-In-Cloud/18-Low-Code/assignment.md +++ b/translations/hi/5-Data-Science-In-Cloud/18-Low-Code/assignment.md @@ -1,12 +1,3 @@ - # Azure ML पर लो कोड/नो कोड डेटा साइंस प्रोजेक्ट ## निर्देश diff --git a/translations/hi/5-Data-Science-In-Cloud/19-Azure/README.md b/translations/hi/5-Data-Science-In-Cloud/19-Azure/README.md index 0e75fbbb..00301cd1 100644 --- a/translations/hi/5-Data-Science-In-Cloud/19-Azure/README.md +++ b/translations/hi/5-Data-Science-In-Cloud/19-Azure/README.md @@ -1,12 +1,3 @@ - # क्लाउड में डेटा साइंस: "Azure ML SDK" का तरीका |![ स्केच नोट [(@sketchthedocs)](https://sketchthedocs.dev) द्वारा ](../../sketchnotes/19-DataScience-Cloud.png)| diff --git a/translations/hi/5-Data-Science-In-Cloud/19-Azure/assignment.md b/translations/hi/5-Data-Science-In-Cloud/19-Azure/assignment.md index fa8d776f..93fe0fc7 100644 --- a/translations/hi/5-Data-Science-In-Cloud/19-Azure/assignment.md +++ b/translations/hi/5-Data-Science-In-Cloud/19-Azure/assignment.md @@ -1,12 +1,3 @@ - # Azure ML SDK का उपयोग करके डेटा साइंस प्रोजेक्ट ## निर्देश diff --git a/translations/hi/5-Data-Science-In-Cloud/README.md b/translations/hi/5-Data-Science-In-Cloud/README.md index d3a50182..cfcc6062 100644 --- a/translations/hi/5-Data-Science-In-Cloud/README.md +++ b/translations/hi/5-Data-Science-In-Cloud/README.md @@ -1,12 +1,3 @@ - # क्लाउड में डेटा साइंस ![cloud-picture](../../../translated_images/hi/cloud-picture.f5526de3c6c6387b2d656ba94f019b3352e5e3854a78440e4fb00c93e2dea675.jpg) diff --git a/translations/hi/6-Data-Science-In-Wild/20-Real-World-Examples/README.md b/translations/hi/6-Data-Science-In-Wild/20-Real-World-Examples/README.md index a7e893f6..fb5c3cc5 100644 --- a/translations/hi/6-Data-Science-In-Wild/20-Real-World-Examples/README.md +++ b/translations/hi/6-Data-Science-In-Wild/20-Real-World-Examples/README.md @@ -1,12 +1,3 @@ - # वास्तविक दुनिया में डेटा विज्ञान | ![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/20-DataScience-RealWorld.png) | diff --git a/translations/hi/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md b/translations/hi/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md index aba775bf..be327e1d 100644 --- a/translations/hi/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md +++ b/translations/hi/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md @@ -1,12 +1,3 @@ - # ग्रह कंप्यूटर डेटा सेट का अन्वेषण करें ## निर्देश diff --git a/translations/hi/6-Data-Science-In-Wild/README.md b/translations/hi/6-Data-Science-In-Wild/README.md index ca3f1082..0c1ad730 100644 --- a/translations/hi/6-Data-Science-In-Wild/README.md +++ b/translations/hi/6-Data-Science-In-Wild/README.md @@ -1,12 +1,3 @@ - # जंगली में डेटा साइंस विभिन्न उद्योगों में डेटा साइंस के वास्तविक दुनिया में उपयोग। diff --git a/translations/hi/AGENTS.md b/translations/hi/AGENTS.md index d9cc81d9..920efe0a 100644 --- a/translations/hi/AGENTS.md +++ b/translations/hi/AGENTS.md @@ -1,12 +1,3 @@ - # AGENTS.md ## परियोजना का अवलोकन diff --git a/translations/hi/CODE_OF_CONDUCT.md b/translations/hi/CODE_OF_CONDUCT.md index c87a3b2f..6049399d 100644 --- a/translations/hi/CODE_OF_CONDUCT.md +++ b/translations/hi/CODE_OF_CONDUCT.md @@ -1,12 +1,3 @@ - # Microsoft ओपन सोर्स आचार संहिता इस प्रोजेक्ट ने [Microsoft ओपन सोर्स आचार संहिता](https://opensource.microsoft.com/codeofconduct/) को अपनाया है। diff --git a/translations/hi/CONTRIBUTING.md b/translations/hi/CONTRIBUTING.md index 1d2b14aa..97dae914 100644 --- a/translations/hi/CONTRIBUTING.md +++ b/translations/hi/CONTRIBUTING.md @@ -1,12 +1,3 @@ - # शुरुआती डेटा साइंस में योगदान करें डेटा साइंस फॉर बिगिनर्स पाठ्यक्रम में योगदान करने में आपकी रुचि के लिए धन्यवाद! हम समुदाय से योगदान का स्वागत करते हैं। diff --git a/translations/hi/INSTALLATION.md b/translations/hi/INSTALLATION.md index baafe52b..e256f1f7 100644 --- a/translations/hi/INSTALLATION.md +++ b/translations/hi/INSTALLATION.md @@ -1,12 +1,3 @@ - # इंस्टॉलेशन गाइड यह गाइड आपको Data Science for Beginners पाठ्यक्रम के साथ काम करने के लिए अपना वातावरण सेट करने में मदद करेगा। diff --git a/translations/hi/README.md b/translations/hi/README.md index c79d7985..c07bffd3 100644 --- a/translations/hi/README.md +++ b/translations/hi/README.md @@ -1,202 +1,193 @@ - -# शुरुआत के लिए डेटा साइंस - एक पाठ्यक्रम - -[![GitHub Codespaces में खोलें](https://github.com/codespaces/badge.svg)](https://github.com/codespaces/new?hide_repo_select=true&ref=main&repo=344191198) - -[![GitHub लाइसेंस](https://img.shields.io/github/license/microsoft/Data-Science-For-Beginners.svg)](https://github.com/microsoft/Data-Science-For-Beginners/blob/master/LICENSE) -[![GitHub योगदानकर्ता](https://img.shields.io/github/contributors/microsoft/Data-Science-For-Beginners.svg)](https://GitHub.com/microsoft/Data-Science-For-Beginners/graphs/contributors/) -[![GitHub मुद्दे](https://img.shields.io/github/issues/microsoft/Data-Science-For-Beginners.svg)](https://GitHub.com/microsoft/Data-Science-For-Beginners/issues/) -[![GitHub पुल रिक्वेस्ट](https://img.shields.io/github/issues-pr/microsoft/Data-Science-For-Beginners.svg)](https://GitHub.com/microsoft/Data-Science-For-Beginners/pulls/) -[![PR स्वागत हैं](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com) - -[![GitHub वॉचर्स](https://img.shields.io/github/watchers/microsoft/Data-Science-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/Data-Science-For-Beginners/watchers/) -[![GitHub फोर्क्स](https://img.shields.io/github/forks/microsoft/Data-Science-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/Data-Science-For-Beginners/network/) -[![GitHub सितारे](https://img.shields.io/github/stars/microsoft/Data-Science-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/Data-Science-For-Beginners/stargazers/) +# शुरुआती के लिए डेटा साइंस - एक पाठ्यक्रम + +[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://github.com/codespaces/new?hide_repo_select=true&ref=main&repo=344191198) + +[![GitHub license](https://img.shields.io/github/license/microsoft/Data-Science-For-Beginners.svg)](https://github.com/microsoft/Data-Science-For-Beginners/blob/master/LICENSE) +[![GitHub contributors](https://img.shields.io/github/contributors/microsoft/Data-Science-For-Beginners.svg)](https://GitHub.com/microsoft/Data-Science-For-Beginners/graphs/contributors/) +[![GitHub issues](https://img.shields.io/github/issues/microsoft/Data-Science-For-Beginners.svg)](https://GitHub.com/microsoft/Data-Science-For-Beginners/issues/) +[![GitHub pull-requests](https://img.shields.io/github/issues-pr/microsoft/Data-Science-For-Beginners.svg)](https://GitHub.com/microsoft/Data-Science-For-Beginners/pulls/) +[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com) + +[![GitHub watchers](https://img.shields.io/github/watchers/microsoft/Data-Science-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/Data-Science-For-Beginners/watchers/) +[![GitHub forks](https://img.shields.io/github/forks/microsoft/Data-Science-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/Data-Science-For-Beginners/network/) +[![GitHub stars](https://img.shields.io/github/stars/microsoft/Data-Science-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/Data-Science-For-Beginners/stargazers/) [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -[![Microsoft Foundry डेवलपर फोरम](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) +[![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) -Microsoft में Azure क्लाउड एडवोकेट्स एक 10-सप्ताह, 20-पाठ्यक्रम की योजना लेकर आए हैं जो पूरी तरह से डेटा साइंस के बारे में है। प्रत्येक पाठ में प्री-लेसन और पोस्ट-लेसन क्विज़, पढ़ाई पूरी करने के लिए लिखित निर्देश, एक समाधान और एक असाइनमेंट शामिल होता है। हमारा परियोजना-आधारित शिक्षण तरीका आपको निर्माण करते हुए सीखने की अनुमति देता है, जो नए कौशल को 'अटकने' का एक प्रमाणित तरीका है। +Microsoft में Azure Cloud Advocates को डेटा साइंस के बारे में 10 सप्ताह, 20-पाठों का पूरा पाठ्यक्रम प्रस्तुत करते हुए खुशी हो रही है। प्रत्येक पाठ में पाठ से पहले और बाद में क्विज, पाठ पूरा करने के लिए लिखित निर्देश, समाधान और असाइनमेंट शामिल हैं। हमारी परियोजना-आधारित शिक्षण पद्धति आपको निर्माण करते हुए सीखने की अनुमति देती है, जो नई क्षमताओं को स्थायी रूप से सीखने का एक प्रमाणित तरीका है। -**हमारे लेखकों को हार्दिक धन्यवाद:** [Jasmine Greenaway](https://www.twitter.com/paladique), [Dmitry Soshnikov](http://soshnikov.com), [Nitya Narasimhan](https://twitter.com/nitya), [Jalen McGee](https://twitter.com/JalenMcG), [Jen Looper](https://twitter.com/jenlooper), [Maud Levy](https://twitter.com/maudstweets), [Tiffany Souterre](https://twitter.com/TiffanySouterre), [Christopher Harrison](https://www.twitter.com/geektrainer)। +**हमारे लेखकों को हार्दिक धन्यवाद:** [Jasmine Greenaway](https://www.twitter.com/paladique), [Dmitry Soshnikov](http://soshnikov.com), [Nitya Narasimhan](https://twitter.com/nitya), [Jalen McGee](https://twitter.com/JalenMcG), [Jen Looper](https://twitter.com/jenlooper), [Maud Levy](https://twitter.com/maudstweets), [Tiffany Souterre](https://twitter.com/TiffanySouterre), [Christopher Harrison](https://www.twitter.com/geektrainer). -**🙏 हमारे [Microsoft Student Ambassador](https://studentambassadors.microsoft.com/) लेखकों, समीक्षकों और कंटेंट योगदानकर्ताओं को विशेष धन्यवाद 🙏,** विशेष रूप से Aaryan Arora, [Aditya Garg](https://github.com/AdityaGarg00), [Alondra Sanchez](https://www.linkedin.com/in/alondra-sanchez-molina/), [Ankita Singh](https://www.linkedin.com/in/ankitasingh007), [Anupam Mishra](https://www.linkedin.com/in/anupam--mishra/), [Arpita Das](https://www.linkedin.com/in/arpitadas01/), ChhailBihari Dubey, [Dibri Nsofor](https://www.linkedin.com/in/dibrinsofor), [Dishita Bhasin](https://www.linkedin.com/in/dishita-bhasin-7065281bb), [Majd Safi](https://www.linkedin.com/in/majd-s/), [Max Blum](https://www.linkedin.com/in/max-blum-6036a1186/), [Miguel Correa](https://www.linkedin.com/in/miguelmque/), [Mohamma Iftekher (Iftu) Ebne Jalal](https://twitter.com/iftu119), [Nawrin Tabassum](https://www.linkedin.com/in/nawrin-tabassum), [Raymond Wangsa Putra](https://www.linkedin.com/in/raymond-wp/), [Rohit Yadav](https://www.linkedin.com/in/rty2423), Samridhi Sharma, [Sanya Sinha](https://www.linkedin.com/mwlite/in/sanya-sinha-13aab1200), -[Sheena Narula](https://www.linkedin.com/in/sheena-narua-n/), [Tauqeer Ahmad](https://www.linkedin.com/in/tauqeerahmad5201/), Yogendrasingh Pawar , [Vidushi Gupta](https://www.linkedin.com/in/vidushi-gupta07/), [Jasleen Sondhi](https://www.linkedin.com/in/jasleen-sondhi/) +**🙏 हमारे [Microsoft Student Ambassador](https://studentambassadors.microsoft.com/) लेखकों, समीक्षकों और सामग्री योगदानकर्ताओं को विशेष धन्यवाद,** विशेष रूप से आर्यन अरोड़ा, [Aditya Garg](https://github.com/AdityaGarg00), [Alondra Sanchez](https://www.linkedin.com/in/alondra-sanchez-molina/), [अंकिता सिंह](https://www.linkedin.com/in/ankitasingh007), [अनुपम मिश्रा](https://www.linkedin.com/in/anupam--mishra/), [अर्पिता दास](https://www.linkedin.com/in/arpitadas01/), छैल बिहारी दुबे, [Dibri Nsofor](https://www.linkedin.com/in/dibrinsofor), [Dishita Bhasin](https://www.linkedin.com/in/dishita-bhasin-7065281bb), [Majd Safi](https://www.linkedin.com/in/majd-s/), [Max Blum](https://www.linkedin.com/in/max-blum-6036a1186/), [Miguel Correa](https://www.linkedin.com/in/miguelmque/), [Mohamma Iftekher (Iftu) Ebne Jalal](https://twitter.com/iftu119), [Nawrin Tabassum](https://www.linkedin.com/in/nawrin-tabassum), [Raymond Wangsa Putra](https://www.linkedin.com/in/raymond-wp/), [Rohit Yadav](https://www.linkedin.com/in/rty2423), समृद्धि शर्मा, [Sanya Sinha](https://www.linkedin.com/mwlite/in/sanya-sinha-13aab1200), +[Sheena Narula](https://www.linkedin.com/in/sheena-narua-n/), [Tauqeer Ahmad](https://www.linkedin.com/in/tauqeerahmad5201/), योगेंद्रसिंह पवार , [Vidushi Gupta](https://www.linkedin.com/in/vidushi-gupta07/), [Jasleen Sondhi](https://www.linkedin.com/in/jasleen-sondhi/) -|![Sketchnote by @sketchthedocs https://sketchthedocs.dev](../../../../translated_images/hi/00-Title.8af36cd35da1ac55.webp)| +|![Sketchnote by @sketchthedocs https://sketchthedocs.dev](../../translated_images/hi/00-Title.8af36cd35da1ac55.webp)| |:---:| -| शुरुआत के लिए डेटा साइंस - _स्केचनोट [@nitya](https://twitter.com/nitya) द्वारा_ | +| शुरुआती के लिए डेटा साइंस - _स्केचनोट [@nitya](https://twitter.com/nitya) द्वारा_ | ### 🌐 बहुभाषी समर्थन #### GitHub Action के माध्यम से समर्थित (स्वचालित और हमेशा अद्यतित) -[Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](./README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../br/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) +[Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh-CN/README.md) | [Chinese (Traditional, Hong Kong)](../zh-HK/README.md) | [Chinese (Traditional, Macau)](../zh-MO/README.md) | [Chinese (Traditional, Taiwan)](../zh-TW/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](./README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../pt-BR/README.md) | [Portuguese (Portugal)](../pt-PT/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) -> **स्थानीय रूप से क्लोन करना पसंद करें?** +> **स्थानीय तौर पर क्लोन करना पसंद करें?** -> इस रिपोजिटरी में 50+ भाषा के अनुवाद शामिल हैं जो डाउनलोड के आकार को काफी बढ़ाते हैं। अनुवादों के बिना क्लोन करने के लिए, sparse checkout का उपयोग करें: +> इस रिपॉजिटरी में 50+ भाषा के अनुवाद शामिल हैं जो डाउनलोड साइज को काफी बढ़ाते हैं। बिना अनुवाद के क्लोन करने के लिए sparse checkout का उपयोग करें: > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/Data-Science-For-Beginners.git > cd Data-Science-For-Beginners > git sparse-checkout set --no-cone '/*' '!translations' '!translated_images' > ``` -> यह आपको पाठ्यक्रम पूरा करने के लिए आवश्यक सब कुछ बहुत तेज़ डाउनलोड के साथ देगा। +> यह आपको बहुत तेज़ डाउनलोड के साथ पाठ्यक्रम पूरा करने के लिए आवश्यक सभी कुछ देता है। -**यदि आप अतिरिक्त भाषाओं का समर्थन चाहते हैं तो वे [यहाँ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) सूचीबद्ध हैं** +**यदि आप अतिरिक्त अनुवाद भाषाओं का समर्थन चाहते हैं तो वे यहाँ सूचीबद्ध हैं [यहाँ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)** #### हमारे समुदाय में शामिल हों [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -हमारे पास Discord पर सीखने के लिए AI श्रृंखला जारी है, इसके बारे में अधिक जानें और 18 - 30 सितंबर, 2025 में [Learn with AI Series](https://aka.ms/learnwithai/discord) में शामिल हों। आपको GitHub Copilot का उपयोग करके डेटा साइंस के टिप्स और ट्रिक्स मिलेंगे। +हमारी Discord पर AI के साथ सीखने की एक श्रृंखला चल रही है, इसके बारे में अधिक जानने और शामिल होने के लिए [Learn with AI Series](https://aka.ms/learnwithai/discord) पर 18 - 30 सितंबर, 2025 आएं। आपको GitHub Copilot के Data Science उपयोग के टिप्स और ट्रिक्स मिलेंगे। -![Learn with AI series](../../../../translated_images/hi/1.2b28cdc6205e26fe.webp) +![Learn with AI series](../../translated_images/hi/1.2b28cdc6205e26fe.webp) -# क्या आप छात्र हैं? +# क्या आप एक छात्र हैं? -निम्न संसाधनों के साथ शुरुआत करें: +निम्नलिखित संसाधनों से शुरुआत करें: -- [Student Hub पेज](https://docs.microsoft.com/en-gb/learn/student-hub?WT.mc_id=academic-77958-bethanycheum) इस पेज में आपको शुरुआती संसाधन, Student पैक और यहां तक कि फ्री सर्टिफिकेट वाउचर पाने के तरीके मिलेंगे। यह एक ऐसा पेज है जिसे आप बुकमार्क करना चाहेंगे और समय-समय पर देखना चाहेंगे क्योंकि हम कम से कम मासिक रूप से सामग्री को बदला करते हैं। -- [Microsoft Learn Student Ambassadors](https://studentambassadors.microsoft.com?WT.mc_id=academic-77958-bethanycheum) ग्लोबल छात्रों के दूतों के समुदाय में शामिल हों, यह Microsoft में आपका मार्ग हो सकता है। +- [Student Hub page](https://docs.microsoft.com/en-gb/learn/student-hub?WT.mc_id=academic-77958-bethanycheum) इस पेज में, आपको शुरुआती संसाधन, छात्र पैक और मुफ्त प्रमाणन वाउचर प्राप्त करने के तरीके मिलेंगे। यह एक ऐसा पेज है जिसे आप बुकमार्क करना चाहेंगे और समय-समय पर जांचते रहना चाहिए क्योंकि हम कम से कम मासिक रूप से सामग्री बदलते रहते हैं। +- [Microsoft Learn Student Ambassadors](https://studentambassadors.microsoft.com?WT.mc_id=academic-77958-bethanycheum) एक वैश्विक छात्र एम्बेसडर समुदाय में शामिल हों, यह Microsoft में आपका रास्ता हो सकता है। -# शुरू करना +# शुरूआत ## 📚 दस्तावेज़ीकरण -- **[इंस्टॉलेशन गाइड](INSTALLATION.md)** - शुरुआती लोगों के लिए चरण-दर-चरण सेटअप निर्देश +- **[इंस्टॉलेशन गाइड](INSTALLATION.md)** - शुरुआती के लिए चरण-दर-चरण सेटअप निर्देश - **[उपयोग गाइड](USAGE.md)** - उदाहरण और सामान्य कार्यप्रवाह -- **[ट्रबलशूटिंग](TROUBLESHOOTING.md)** - सामान्य समस्याओं के समाधान -- **[योगदान देने का गाइड](CONTRIBUTING.md)** - इस परियोजना में योगदान कैसे करें +- **[समस्या निवारण](TROUBLESHOOTING.md)** - सामान्य समस्याओं के समाधान +- **[योगदान गाइड](CONTRIBUTING.md)** - इस प्रोजेक्ट में योगदान कैसे करें - **[शिक्षकों के लिए](for-teachers.md)** - शिक्षण मार्गदर्शन और कक्षा संसाधन ## 👨‍🎓 छात्रों के लिए -> **पूरी तरह से शुरुआती**: डेटा साइंस में नए हैं? हमारी [शुरुआती अनुकूल उदाहरण](examples/README.md) से शुरू करें! ये सरल, अच्छी तरह से कॉमेंट किए गए उदाहरण आपको पूरी पाठ्यक्रम में उतरने से पहले मूल बातें समझने में मदद करेंगे। -> **[छात्र](https://aka.ms/student-page)**: इस पाठ्यक्रम को स्वयं उपयोग करने के लिए, पूरे रिपो को फोर्क करें और स्वयं अभ्यास पूरा करें, प्री-लेक्चर क्विज़ से शुरू करें। फिर लेक्चर पढ़ें और बाकी गतिविधियाँ पूरी करें। समाधान कोड की नकल करने के बजाय पाठों को समझकर परियोजनाएँ बनाने का प्रयास करें; हालांकि, वह कोड प्रत्येक परियोजना-उन्मुख पाठ में /solutions फोल्डर में उपलब्ध है। एक और विचार यह हो सकता है कि दोस्तों के साथ अध्ययन समूह बनाकर सामग्री को एक साथ देखें। और अधिक अध्ययन के लिए, हम [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/qprpajyoy3x0g7?WT.mc_id=academic-77958-bethanycheum) की सलाह देते हैं। +> **पूर्ण शुरुआती**: डेटा साइंस में नए हैं? हमारे [शुरुआती-फ्रेंडली उदाहरणों](examples/README.md) से शुरुआत करें! ये सरल, अच्छी तरह से कमेंट किए गए उदाहरण आपको पूरा पाठ्यक्रम शुरू करने से पहले बुनियादी बातें समझने में मदद करेंगे। +> **[छात्र](https://aka.ms/student-page)**: इस पाठ्यक्रम का उपयोग अपने आप करने के लिए, पूरा रिपॉजिटरी फोर्क करें और अपनी ओर से अभ्यास पूरा करें, प्री-लेक्चर क्विज से शुरू करें। फिर व्याख्यान पढ़ें और बाकी गतिविधियां पूरी करें। परियोजनाओं को समाधान कोड की नकल करने के बजाय पाठों को समझकर बनाने की कोशिश करें; हालांकि, वह कोड प्रत्येक परियोजना-उन्मुख पाठ के /solutions फोल्डरों में उपलब्ध है। एक और विचार यह हो सकता है कि दोस्तों के साथ एक अध्ययन समूह बनाएं और सामग्री एक साथ पढ़ें। आगे अध्ययन के लिए, हम [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/qprpajyoy3x0g7?WT.mc_id=academic-77958-bethanycheum) की सलाह देते हैं। **त्वरित शुरुआत:** -1. अपना पर्यावरण सेटअप करने के लिए [इंस्टॉलेशन गाइड](INSTALLATION.md) देखें -2. पाठ्यक्रम के साथ काम करने के लिए [उपयोग गाइड](USAGE.md) देखें -3. पाठ 1 से शुरू करें और क्रमशः पूरा करें -4. सहायता के लिए हमारे [Discord समुदाय](https://aka.ms/ds4beginners/discord) में शामिल हों +1. अपनी पर्यावरण सेटअप के लिए [इंस्टॉलेशन गाइड](INSTALLATION.md) देखें +2. पाठ्यक्रम के साथ काम करने के लिए [उपयोग गाइड](USAGE.md) पढ़ें +3. पाठ 1 से शुरू करें और क्रमबद्ध रूप से कार्य करें +4. समर्थन के लिए हमारे [Discord समुदाय](https://aka.ms/ds4beginners/discord) में शामिल हों ## 👩‍🏫 शिक्षकों के लिए -> **शिक्षक**: हमने [इस पाठ्यक्रम का उपयोग कैसे करें](for-teachers.md) पर कुछ सुझाव शामिल किए हैं। हम आपकी प्रतिक्रिया [हमारे चर्चा मंच पर](https://github.com/microsoft/Data-Science-For-Beginners/discussions) सुनना चाहेंगे! - +> **शिक्षक**: हमने इस पाठ्यक्रम का उपयोग कैसे किया जाए इसके बारे में [कुछ सुझाव](for-teachers.md) शामिल किए हैं। हम आपकी प्रतिक्रियाओं के लिए उत्सुक हैं [हमारे चर्चा मंच में](https://github.com/microsoft/Data-Science-For-Beginners/discussions)! ## टीम से मिलें -[![Promo video](../../ds-for-beginners.gif)](https://youtu.be/8mzavjQSMM4 "Promo video") -**Gif द्वारा** [Mohit Jaisal](https://www.linkedin.com/in/mohitjaisal) +[![प्रोमो वीडियो](../../ds-for-beginners.gif)](https://youtu.be/8mzavjQSMM4 "प्रोमो वीडियो") + +**गिफ़ द्वारा** [मोहित जैसल](https://www.linkedin.com/in/mohitjaisal) -> 🎥 ऊपर दी गई छवि पर क्लिक करें एक वीडियो के लिए जो इस परियोजना और इसे निर्माण करने वालों के बारे में है! +> 🎥 परियोजना और इसे बनाने वाले लोगों के बारे में वीडियो के लिए ऊपर की छवि पर क्लिक करें! -## शिक्षा शास्त्र +## शिक्षाशास्त्र -हमने इस पाठ्यक्रम को बनाते समय दो शैक्षिक सिद्धांतों को चुना है: यह सुनिश्चित करना कि यह परियोजना-आधारित हो और इसमें बार-बार क्विज़ शामिल हों। इस श्रृंखला के अंत तक, छात्र डेटा विज्ञान के मूलभूत सिद्धांतों को सीख चुके होंगे, जिसमें नैतिक अवधारणाएँ, डेटा तैयारी, डेटा के साथ काम करने के विभिन्न तरीके, डेटा विजुअलाइज़ेशन, डेटा विश्लेषण, डेटा विज्ञान के वास्तविक दुनिया के उपयोग मामले, और अधिक शामिल हैं। +हमने इस पाठ्यक्रम को बनाते समय दो शिक्षाशास्त्रीय सिद्धांत चुने हैं: यह सुनिश्चित करना कि यह परियोजना-आधारित हो और इसमें अक्सर क्विज़ शामिल हों। इस श्रृंखला के अंत तक, छात्र डेटा विज्ञान के मूल सिद्धांतों को सीखेंगे, जिनमें नैतिक अवधारणाएं, डेटा तैयारी, डेटा के साथ काम करने के विभिन्न तरीके, डेटा विज़ुअलाइज़ेशन, डेटा विश्लेषण, डेटा विज्ञान के वास्तविक दुनिया उपयोग के मामले, और अधिक शामिल हैं। -इसके अलावा, कक्षा से पहले एक कम दबाव वाला क्विज़ छात्र के विषय सीखने की इच्छा को सेट करता है, जबकि कक्षा के बाद दूसरा क्विज़ और अधिक अवधारण सुनिश्चित करता है। यह पाठ्यक्रम लचीला और मजेदार बनाने के लिए डिज़ाइन किया गया है और इसे पूरी तरह या आंशिक रूप से लिया जा सकता है। परियोजनाएँ छोटी शुरू होती हैं और 10 सप्ताह के चक्र के अंत तक बढ़ती जटिल होती जाती हैं। +इसके अलावा, कक्षा से पहले एक कम-जिम्मेदारी वाला क्विज़ छात्र के सीखने के इरादे को सेट करता है, जबकि कक्षा के बाद दूसरा क्विज़ और अधिक अवधारण सुनिश्चित करता है। यह पाठ्यक्रम लचीला और मजेदार बनाया गया है और इसे पूरी तरह या आंशिक रूप से लिया जा सकता है। परियोजनाएं छोटी से शुरू होती हैं और 10 सप्ताह के चक्र के अंत तक क्रमिक रूप से जटिल हो जाती हैं। -> हमारा [आचरण संहिता](CODE_OF_CONDUCT.md), [योगदान](CONTRIBUTING.md), [अनुवाद](TRANSLATIONS.md) दिशानिर्देश देखें। हम आपकी रचनात्मक प्रतिक्रिया का स्वागत करते हैं! +> हमारे [आचार संहिता](CODE_OF_CONDUCT.md), [योगदान](CONTRIBUTING.md), [अनुवाद](TRANSLATIONS.md) दिशानिर्देश देखें। हम आपकी रचनात्मक प्रतिक्रिया का स्वागत करते हैं! -## प्रत्येक पाठ में शामिल हैं: +## प्रत्येक पाठ में शामिल है: - वैकल्पिक स्केचनोट - वैकल्पिक सहायक वीडियो -- कक्षा से पहले वार्मअप क्विज़ -- लिखित पाठ -- परियोजना-आधारित पाठों के लिए परियोजना बनाने के चरण-दर-चरण मार्गदर्शक +- प्री-लेसन वार्मअप क्विज़ +- लेखित पाठ +- परियोजना-आधारित पाठों के लिए, परियोजना बनाने के चरण-दर-चरण मार्गदर्शिकाएँ - ज्ञान जांच - एक चुनौती -- सहायक पठन सामग्री +- सहायक पठन - असाइनमेंट - [पाठ के बाद क्विज़](https://ff-quizzes.netlify.app/en/) -> **क्विज़ के बारे में एक नोट**: सभी क्विज़ क्विज-एप फोल्डर में संग्रहीत हैं, कुल 40 क्विज़ जिसमें प्रत्येक में तीन प्रश्न हैं। इन्हें पाठों से लिंक किया गया है, लेकिन क्विज ऐप को स्थानीय रूप से चलाया जा सकता है या Azure पर तैनात किया जा सकता है; इसके लिए `quiz-app` फोल्डर में निर्देश देखें। इन्हें धीरे-धीरे स्थानीयकृत किया जा रहा है। +> **क्विज़ के बारे में एक नोट**: सभी क्विज़ क्विज़-एप फ़ोल्डर में संग्रहीत हैं, जिसमें तीन प्रश्नों के 40 कुल क्विज़ शामिल हैं। ये पाठों के अंदर लिंक किए गए हैं, लेकिन क्विज़ ऐप को स्थानीय रूप से चलाया जा सकता है या Azure पर तैनात किया जा सकता है; निर्देशों के लिए `quiz-app` फ़ोल्डर देखें। इन्हें धीरे-धीरे स्थानीयकृत किया जा रहा है। -## 🎓 शुरुआती के लिए सहायक उदाहरण +## 🎓 शुरुआती-अनुकूल उदाहरण -**डेटा विज्ञान में नए हैं?** हमने एक विशेष [examples directory](examples/README.md) बनाया है जिसमें सरल, अच्छी तरह से टिप्पणी किया गया कोड है ताकि आप शुरू कर सकें: +**डेटा साइंस में नए हैं?** हमने एक विशेष [उदाहरण निर्देशिका](examples/README.md) बनाई है जिसमें सरल, अच्छी तरह से टिप्पणीकृत कोड है जो आपको शुरुआत करने में मदद करता है: -- 🌟 **Hello World** - आपका पहला डेटा विज्ञान प्रोग्राम -- 📂 **डेटा लोड करना** - डेटा सेट पढ़ना और अन्वेषण करना सीखें -- 📊 **सरल विश्लेषण** - सांख्यिकी की गणना करें और पैटर्न खोजें -- 📈 **मूल विज़ुअलाइज़ेशन** - चार्ट और ग्राफ बनाएं -- 🔬 **वास्तविक परियोजना** - शुरुआत से अंत तक पूरा वर्कफ़्लो +- 🌟 **हैलो वर्ल्ड** - आपका पहला डेटा विज्ञान प्रोग्राम +- 📂 **लोडिंग डेटा** - डेटासेट पढ़ना और एक्सप्लोर करना सीखें +- 📊 **सरल विश्लेषण** - सांख्यिकीय गणना करें और पैटर्न खोजें +- 📈 **मूल विज़ुअलाइज़ेशन** - चार्ट और ग्राफ़ बनाएं +- 🔬 **वास्तविक-दुनिया परियोजना** - शुरुआत से अंत तक पूरा कार्यप्रवाह -प्रत्येक उदाहरण में विस्तृत टिप्पणियाँ शामिल हैं जो हर कदम को समझाती हैं, जिससे यह पूर्ण शुरुआती लोगों के लिए आदर्श है! +प्रत्येक उदाहरण में हर चरण को समझाने वाली विस्तृत टिप्पणियाँ शामिल हैं, जो इसे पूर्ण शुरुआती के लिए उपयुक्त बनाती हैं! -👉 **[उदाहरणों के साथ शुरुआत करें](examples/README.md)** 👈 +👉 **[उदाहरणों से शुरू करें](examples/README.md)** 👈 ## पाठ -|![ Sketchnote by @sketchthedocs https://sketchthedocs.dev](../../../../translated_images/hi/00-Roadmap.4905d6567dff4753.webp)| +|![ @sketchthedocs द्वारा स्केचनोट https://sketchthedocs.dev](../../translated_images/hi/00-Roadmap.4905d6567dff4753.webp)| |:---:| -| डेटा विज्ञान के लिए शुरुआती: रोडमैप - _स्केचनोट द्वारा [@nitya](https://twitter.com/nitya)_ | +| डेटा साइंस फॉर बिगिनर्स: रोडमैप - _स्केचनोट द्वारा [@nitya](https://twitter.com/nitya)_ | -| पाठ संख्या | विषय | पाठ समूह | शिक्षण उद्देश्य | लिंक्ड पाठ | लेखक | +| पाठ संख्या | विषय | पाठ समूह | सीखने के उद्देश्य | लिंक्ड पाठ | लेखक | | :-----------: | :----------------------------------------: | :--------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------: | :----: | -| 01 | डेटा विज्ञान की परिभाषा | [परिचय](1-Introduction/README.md) | डेटा विज्ञान के मूलभूत सिद्धांत सीखें और यह कैसे कृत्रिम बुद्धिमत्ता, मशीन लर्निंग, और बिग डेटा से जुड़ा है। | [पाठ](1-Introduction/01-defining-data-science/README.md) [वीडियो](https://youtu.be/beZ7Mb_oz9I) | [दिमित्री](http://soshnikov.com) | -| 02 | डेटा विज्ञान नैतिकता | [परिचय](1-Introduction/README.md) | डेटा नैतिकता अवधारणाएँ, चुनौतियाँ और फ्रेमवर्क। | [पाठ](1-Introduction/02-ethics/README.md) | [नित्या](https://twitter.com/nitya) | +| 01 | डेटा साइंस की परिभाषा | [परिचय](1-Introduction/README.md) | डेटा विज्ञान के पीछे के मूल सिद्धांतों को जानें और यह कृत्रिम बुद्धिमत्ता, मशीन लर्निंग, और बड़े डेटा से कैसे जुड़ा है। | [पाठ](1-Introduction/01-defining-data-science/README.md) [विडियो](https://youtu.be/beZ7Mb_oz9I) | [द्मित्री](http://soshnikov.com) | +| 02 | डेटा साइंस नैतिकता | [परिचय](1-Introduction/README.md) | डेटा नैतिकता के संकल्पनाएँ, चुनौतियाँ और ढाँचे। | [पाठ](1-Introduction/02-ethics/README.md) | [नित्य](https://twitter.com/nitya) | | 03 | डेटा की परिभाषा | [परिचय](1-Introduction/README.md) | डेटा कैसे वर्गीकृत किया जाता है और इसके सामान्य स्रोत। | [पाठ](1-Introduction/03-defining-data/README.md) | [जैस्मिन](https://www.twitter.com/paladique) | -| 04 | सांख्यिकी और प्रायिकता परिचय | [परिचय](1-Introduction/README.md) | डेटा को समझने के लिए प्रायिकता और सांख्यिकी की गणितीय तकनीकें। | [पाठ](1-Introduction/04-stats-and-probability/README.md) [वीडियो](https://youtu.be/Z5Zy85g4Yjw) | [दिमित्री](http://soshnikov.com) | -| 05 | रिलेशनल डेटा के साथ काम करना | [डेटा के साथ काम करना](2-Working-With-Data/README.md) | रिलेशनल डेटा का परिचय और SQL (जिसे “सी-क्वेल” कहा जाता है) के साथ रिलेशनल डेटा का अन्वेषण और विश्लेषण करने की मूल बातें। | [पाठ](2-Working-With-Data/05-relational-databases/README.md) | [क्रिस्टोफर](https://www.twitter.com/geektrainer) | | | -| 06 | NoSQL डेटा के साथ काम करना | [डेटा के साथ काम करना](2-Working-With-Data/README.md) | अप्रासंगिक डेटा का परिचय, इसके विभिन्न प्रकार और दस्तावेज़ डेटाबेस का अन्वेषण और विश्लेषण करने के मूल बातें। | [पाठ](2-Working-With-Data/06-non-relational/README.md) | [जैस्मिन](https://twitter.com/paladique)| -| 07 | पायथन के साथ काम करना | [डेटा के साथ काम करना](2-Working-With-Data/README.md) | डेटा अन्वेषण के लिए पायथन का उपयोग करने की मूल बातें जैसे Pandas. पायथन प्रोग्रामिंग की मूल समझ की सिफारिश की जाती है। | [पाठ](2-Working-With-Data/07-python/README.md) [वीडियो](https://youtu.be/dZjWOGbsN4Y) | [दिमित्री](http://soshnikov.com) | -| 08 | डेटा तैयारी | [डेटा के साथ काम करना](2-Working-With-Data/README.md) | डेटा की सफाई और रूपांतरण के लिए तकनीकों पर विषय जो गुम, गलत या अधूरा डेटा संभालने की चुनौतियों को हल करते हैं। | [पाठ](2-Working-With-Data/08-data-preparation/README.md) | [जैस्मिन](https://www.twitter.com/paladique) | -| 09 | परिमाणों का विज़ुअलाइज़ेशन | [डेटा विज़ुअलाइज़ेशन](3-Data-Visualization/README.md) | Matplotlib का उपयोग कर पक्षी डेटा को विज़ुअलाइज़ करना सीखें 🦆 | [पाठ](3-Data-Visualization/09-visualization-quantities/README.md) | [जेन](https://twitter.com/jenlooper) | -| 10 | डेटा वितरण का विज़ुअलाइज़ेशन | [डेटा विज़ुअलाइज़ेशन](3-Data-Visualization/README.md) | किसी अंतराल के भीतर अवलोकनों और रुझानों का विज़ुअलाइज़ेशन। | [पाठ](3-Data-Visualization/10-visualization-distributions/README.md) | [जेन](https://twitter.com/jenlooper) | -| 11 | अनुपात का विज़ुअलाइज़ेशन | [डेटा विज़ुअलाइज़ेशन](3-Data-Visualization/README.md) | भिन्न और समूहित प्रतिशत का विज़ुअलाइज़ेशन। | [पाठ](3-Data-Visualization/11-visualization-proportions/README.md) | [जेन](https://twitter.com/jenlooper) | -| 12 | संबंधों का विज़ुअलाइज़ेशन | [डेटा विज़ुअलाइज़ेशन](3-Data-Visualization/README.md) | डेटा सेटों और उनके वेरिएबल्स के बीच कनेक्शन और सहसंबंध का विज़ुअलाइज़ेशन। | [पाठ](3-Data-Visualization/12-visualization-relationships/README.md) | [जेन](https://twitter.com/jenlooper) | -| 13 | सार्थक विज़ुअलाइज़ेशन | [डेटा विज़ुअलाइज़ेशन](3-Data-Visualization/README.md) | प्रभावी समस्या समाधान और अंतर्दृष्टि के लिए अपने विज़ुअलाइज़ेशन को मूल्यवान बनाने के लिए तकनीकें और मार्गदर्शन। | [पाठ](3-Data-Visualization/13-meaningful-visualizations/README.md) | [जेन](https://twitter.com/jenlooper) | -| 14 | डेटा विज्ञान जीवन चक्र परिचय | [जीवनचक्र](4-Data-Science-Lifecycle/README.md) | डेटा विज्ञान जीवन चक्र का परिचय और डेटा प्राप्त करने व निकालने का पहला चरण। | [पाठ](4-Data-Science-Lifecycle/14-Introduction/README.md) | [जैस्मिन](https://twitter.com/paladique) | -| 15 | विश्लेषण | [जीवनचक्र](4-Data-Science-Lifecycle/README.md) | डेटा विज्ञान जीवन चक्र का यह चरण डेटा का विश्लेषण करने तकनीकों पर केंद्रित है। | [पाठ](4-Data-Science-Lifecycle/15-analyzing/README.md) | [जैस्मिन](https://twitter.com/paladique) | | | -| 16 | संचार | [जीवनचक्र](4-Data-Science-Lifecycle/README.md) | इस चरण में डेटा से मिली अंतर्दृष्टि को इस तरह प्रस्तुत करना होता है कि निर्णय निर्माताओं के लिए समझना आसान हो। | [पाठ](4-Data-Science-Lifecycle/16-communication/README.md) | [जालेन](https://twitter.com/JalenMcG) | | | -| 17 | क्लाउड में डेटा विज्ञान | [क्लाउड डेटा](5-Data-Science-In-Cloud/README.md) | क्लाउड में डेटा विज्ञान और इसके लाभों का परिचय। | [पाठ](5-Data-Science-In-Cloud/17-Introduction/README.md) | [टिफ़नी](https://twitter.com/TiffanySouterre) और [मॉड](https://twitter.com/maudstweets) | -| 18 | क्लाउड में डेटा विज्ञान | [क्लाउड डेटा](5-Data-Science-In-Cloud/README.md) | लो कोड टूल्स का उपयोग कर मॉडल का प्रशिक्षण। |[पाठ](5-Data-Science-In-Cloud/18-Low-Code/README.md) | [टिफ़नी](https://twitter.com/TiffanySouterre) और [मॉड](https://twitter.com/maudstweets) | -| 19 | क्लाउड में डेटा विज्ञान | [क्लाउड डेटा](5-Data-Science-In-Cloud/README.md) | Azure मशीन लर्निंग स्टूडियो के साथ मॉडल तैनात करना। | [पाठ](5-Data-Science-In-Cloud/19-Azure/README.md)| [टिफ़नी](https://twitter.com/TiffanySouterre) और [मॉड](https://twitter.com/maudstweets) | -| 20 | डेटा विज्ञान जंगली में | [जंगली में](6-Data-Science-In-Wild/README.md) | वास्तविक दुनिया में डेटा विज्ञान संचालित परियोजनाएं। | [पाठ](6-Data-Science-In-Wild/20-Real-World-Examples/README.md) | [नित्या](https://twitter.com/nitya) | +| 04 | सांख्यिकी और प्रायिकता का परिचय | [परिचय](1-Introduction/README.md) | डेटा को समझने के लिए प्रायिकता और सांख्यिकी की गणितीय तकनीकें। | [पाठ](1-Introduction/04-stats-and-probability/README.md) [विडियो](https://youtu.be/Z5Zy85g4Yjw) | [द्मित्री](http://soshnikov.com) | +| 05 | रिलेशनल डेटा के साथ काम करना | [डेटा के साथ काम करना](2-Working-With-Data/README.md) | रिलेशनल डेटा का परिचय और संरचित क्वेरी भाषा (SQL) के साथ डेटाबेस को एक्सप्लोर और विश्लेषण के मूल बातें। | [पाठ](2-Working-With-Data/05-relational-databases/README.md) | [क्रिस्टोफर](https://www.twitter.com/geektrainer) | | | +| 06 | नोSQL डेटा के साथ काम करना | [डेटा के साथ काम करना](2-Working-With-Data/README.md) | गैर-रिलेशनल डेटा का परिचय, इसके विभिन्न प्रकार और दस्तावेज़ डेटाबेस का अन्वेषण और विश्लेषण। | [पाठ](2-Working-With-Data/06-non-relational/README.md) | [जैस्मिन](https://twitter.com/paladique)| +| 07 | पाइथन के साथ काम करना | [डेटा के साथ काम करना](2-Working-With-Data/README.md) | पांडा जैसी लाइब्रेरीज़ के साथ डेटा अन्वेषण के लिए पाइथन का उपयोग करना। पाइथन प्रोग्रामिंग की आधारभूत समझ की सिफारिश की जाती है। | [पाठ](2-Working-With-Data/07-python/README.md) [विडियो](https://youtu.be/dZjWOGbsN4Y) | [द्मित्री](http://soshnikov.com) | +| 08 | डेटा तैयारी | [डेटा के साथ काम करना](2-Working-With-Data/README.md) | गायब, गलत या अपूर्ण डेटा से निपटने के लिए डेटा की सफाई और रूपांतरण की तकनीकें। | [पाठ](2-Working-With-Data/08-data-preparation/README.md) | [जैस्मिन](https://www.twitter.com/paladique) | +| 09 | मात्राओं का विज़ुअलाइज़ेशन | [डेटा विज़ुअलाइज़ेशन](3-Data-Visualization/README.md) | मैटलैब का उपयोग करके पक्षी डेटा का विज़ुअलाइज़ेशन सीखें 🦆 | [पाठ](3-Data-Visualization/09-visualization-quantities/README.md) | [जेन](https://twitter.com/jenlooper) | +| 10 | डेटा के वितरण का विज़ुअलाइज़ेशन | [डेटा विज़ुअलाइज़ेशन](3-Data-Visualization/README.md) | एक अंतराल के भीतर अवलोकनों और रुझानों का विज़ुअलाइज़ेशन। | [पाठ](3-Data-Visualization/10-visualization-distributions/README.md) | [जेन](https://twitter.com/jenlooper) | +| 11 | अनुपातों का विज़ुअलाइज़ेशन | [डेटा विज़ुअलाइज़ेशन](3-Data-Visualization/README.md) | भिन्न और समूहबद्ध प्रतिशत का विज़ुअलाइज़ेशन। | [पाठ](3-Data-Visualization/11-visualization-proportions/README.md) | [जेन](https://twitter.com/jenlooper) | +| 12 | संबंधों का विज़ुअलाइज़ेशन | [डेटा विज़ुअलाइज़ेशन](3-Data-Visualization/README.md) | डेटा सेट और उनके वेरिएबल्स के बीच कनेक्शन और सहसंबंध का विज़ुअलाइज़ेशन। | [पाठ](3-Data-Visualization/12-visualization-relationships/README.md) | [जेन](https://twitter.com/jenlooper) | +| 13 | अर्थपूर्ण विज़ुअलाइज़ेशन | [डेटा विज़ुअलाइज़ेशन](3-Data-Visualization/README.md) | आपकी विज़ुअलाइज़ेशन को प्रभावी समस्या समाधान और अंतर्दृष्टि के लिए मूल्यवान बनाने की तकनीकें और मार्गदर्शन। | [पाठ](3-Data-Visualization/13-meaningful-visualizations/README.md) | [जेन](https://twitter.com/jenlooper) | +| 14 | डेटा साइंस जीवनचक्र का परिचय | [जीवनचक्र](4-Data-Science-Lifecycle/README.md) | डेटा साइंस जीवनचक्र का परिचय और पहला चरण डेटा अधिग्रहण और निष्कर्षण। | [पाठ](4-Data-Science-Lifecycle/14-Introduction/README.md) | [जैस्मिन](https://twitter.com/paladique) | +| 15 | विश्लेषण करना | [जीवनचक्र](4-Data-Science-Lifecycle/README.md) | डेटा साइंस जीवनचक्र का यह चरण डेटा का विश्लेषण करने की तकनीकों पर केंद्रित है। | [पाठ](4-Data-Science-Lifecycle/15-analyzing/README.md) | [जैस्मिन](https://twitter.com/paladique) | | | +| 16 | संचार | [जीवनचक्र](4-Data-Science-Lifecycle/README.md) | डेटा के निष्कर्षों को इस तरह प्रस्तुत करना ताकि निर्णय लेने वालों के लिए समझना आसान हो। | [पाठ](4-Data-Science-Lifecycle/16-communication/README.md) | [जालेन](https://twitter.com/JalenMcG) | | | +| 17 | क्लाउड में डेटा साइंस | [क्लाउड डेटा](5-Data-Science-In-Cloud/README.md) | क्लाउड में डेटा साइंस और इसके लाभों का परिचय। | [पाठ](5-Data-Science-In-Cloud/17-Introduction/README.md) | [टिफ़नी](https://twitter.com/TiffanySouterre) और [मौड](https://twitter.com/maudstweets) | +| 18 | क्लाउड में डेटा साइंस | [क्लाउड डेटा](5-Data-Science-In-Cloud/README.md) | लो कोड टूल्स का उपयोग कर मॉडल प्रशिक्षण। |[पाठ](5-Data-Science-In-Cloud/18-Low-Code/README.md) | [टिफ़नी](https://twitter.com/TiffanySouterre) और [मौड](https://twitter.com/maudstweets) | +| 19 | क्लाउड में डेटा साइंस | [क्लाउड डेटा](5-Data-Science-In-Cloud/README.md) | Azure मशीन लर्निंग स्टूडियो के साथ मॉडल तैनात करना। | [पाठ](5-Data-Science-In-Cloud/19-Azure/README.md)| [टिफ़नी](https://twitter.com/TiffanySouterre) और [मौड](https://twitter.com/maudstweets) | +| 20 | वाइल्ड में डेटा साइंस | [वाइल्ड में](6-Data-Science-In-Wild/README.md) | वास्तविक दुनिया में डेटा साइंस संचालित परियोजनाएं। | [पाठ](6-Data-Science-In-Wild/20-Real-World-Examples/README.md) | [नित्य](https://twitter.com/nitya) | ## GitHub Codespaces -इस नमूने को एक Codespace में खोलने के लिए ये कदम अपनाएं: +इस नमूने को Codespace में खोलने के लिए ये कदम उठाएं: 1. कोड ड्रॉप-डाउन मेनू पर क्लिक करें और Open with Codespaces विकल्प चुनें। -2. पैन के नीचे + New codespace चुनें। -अधिक जानकारी के लिए, [GitHub डाक्यूमेंटेशन](https://docs.github.com/en/codespaces/developing-in-codespaces/creating-a-codespace-for-a-repository#creating-a-codespace) देखें। +2. पैनल के नीचे + New codespace चुनें। +अधिक जानकारी के लिए, [GitHub दस्तावेज़ीकरण](https://docs.github.com/en/codespaces/developing-in-codespaces/creating-a-codespace-for-a-repository#creating-a-codespace) देखें। ## VSCode Remote - Containers -अपनी स्थानीय मशीन और VSCode का उपयोग करके इस रिपॉजिटरी को कंटेनर में खोलने के लिए ये कदम अपनाएं, VS Code Remote - Containers एक्सटेंशन के साथ: +VSCode Remote - Containers एक्सटेंशन का उपयोग करके अपने स्थानीय मशीन पर कंटेनर में इस रिपॉजिटरी को खोलने के लिए निम्नलिखित करें: -1. यदि यह आपका पहला बार है जब आप विकास कंटेनर का उपयोग कर रहे हैं, तो कृपया सुनिश्चित करें कि आपकी सिस्टम प्री-रिक्विसिट्स को पूरा करती है (जैसे Docker इंस्टॉल हो) [शुरुआत करने की डाक्यूमेंटेशन](https://code.visualstudio.com/docs/devcontainers/containers#_getting-started) में। +1. यदि यह आपका पहला बार है कंटेनर विकास का उपयोग करने का, तो कृपया सुनिश्चित करें कि आपकी प्रणाली आवश्यक शर्तें (जैसे Docker स्थापित है) पूरी करती है [प्रारंभिक दस्तावेज़](https://code.visualstudio.com/docs/devcontainers/containers#_getting-started) में। इस रिपॉजिटरी का उपयोग करने के लिए, आप या तो रिपॉजिटरी को एक अलग Docker वॉल्यूम में खोल सकते हैं: -**नोट**: यह वास्तव में Remote-Containers: **Clone Repository in Container Volume...** कमांड का उपयोग करेगा ताकि स्रोत कोड लोकल फाइल सिस्टम में न बल्कि Docker वॉल्यूम में क्लोन हो। [वॉल्यूम](https://docs.docker.com/storage/volumes/) कंटेनर डेटा को सुरक्षित रखने के लिए प्राथमिक तरीका हैं। +**ध्यान दें**: इसके अंतर्गत, Remote-Containers: **Clone Repository in Container Volume...** कमांड का उपयोग करके सोर्स कोड को लोकल फाइल सिस्टम के बजाय Docker वॉल्यूम में क्लोन किया जाएगा। [वॉल्यूम](https://docs.docker.com/storage/volumes/) कंटेनर डेटा को बनाए रखने के लिए प्राथमिक उपाय हैं। -या रिपॉजिटरी की स्थानीय रूप से क्लोन की हुई या डाउनलोड की हुई कॉपी खोलें: +या एक स्थानीय क्लोन की गई या डाउनलोड की गई प्रति खोलें: -- इस रिपॉजिटरी को अपनी स्थानीय फ़ाइल प्रणाली में क्लोन करें। -- F1 दबाएँ और **Remote-Containers: Open Folder in Container...** कमांड चुनें। -- इस फ़ोल्डर की क्लोन की गई कॉपी चुनें, कंटेनर शुरू होने तक प्रतीक्षा करें, और प्रयोग करें। +- इस रिपॉजिटरी को अपनी स्थानीय फाइल सिस्टम पर क्लोन करें। +- F1 दबाएं और **Remote-Containers: Open Folder in Container...** कमांड चुनें। +- इस फोल्डर की क्लोन की गई प्रति चुनें, कंटेनर के शुरू होने तक प्रतीक्षा करें, और प्रयोग करें। -## ऑफ़लाइन पहुँच +## ऑफ़लाइन एक्सेस -आप इस दस्तावेज़ को ऑफ़लाइन [Docsify](https://docsify.js.org/#/) का उपयोग करके चला सकते हैं। इस रिपॉजिटरी को फोर्क करें, अपनी स्थानीय मशीन पर [Docsify इंस्टॉल करें](https://docsify.js.org/#/quickstart), फिर इस रिपॉजिटरी के रूट फ़ोल्डर में `docsify serve` टाइप करें। वेबसाइट आपके लोकलहोस्ट के पोर्ट 3000 पर सेवा प्रदत्त होगी: `localhost:3000`. +आप इस प्रलेखन को ऑफ़लाइन [Docsify](https://docsify.js.org/#/) का उपयोग करके चला सकते हैं। इस रिपॉजिटरी को फोर्क करें, अपने स्थानीय मशीन पर [Docsify इंस्टॉल करें](https://docsify.js.org/#/quickstart), फिर इस रिपॉजिटरी के रूट फ़ोल्डर में `docsify serve` टाइप करें। वेबसाइट स्थानीयहोस्ट पर पोर्ट 3000 पर सर्व की जाएगी: `localhost:3000`. -> ध्यान दें, नोटबुक Docsify के माध्यम से प्रस्तुत नहीं होंगे, इसलिए जब आपको नोटबुक चलाने की आवश्यकता हो, तो उसे अलग से VS Code में Python कर्नेल चलाकर करें। +> ध्यान दें, नोटबुक Docsify द्वारा रेंडर नहीं होंगे, इसलिए जब आपको कोई नोटबुक चलानी हो, तो वह अलग से VS Code में पाइथन कर्नेल के साथ करें। ## अन्य पाठ्यक्रम @@ -204,7 +195,7 @@ Microsoft में Azure क्लाउड एडवोकेट्स एक ### LangChain -[![LangChain4j for Beginners](https://img.shields.io/badge/LangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchain4j-for-beginners) +[![शुरुआती के लिए LangChain4j](https://img.shields.io/badge/LangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchain4j-for-beginners) [![LangChain.js for Beginners](https://img.shields.io/badge/LangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin) --- @@ -217,7 +208,7 @@ Microsoft में Azure क्लाउड एडवोकेट्स एक --- -### जनरेटिव AI श्रृंखला +### जेनरेटिव AI सीरीज़ [![Generative AI for Beginners](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) [![Generative AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) [![Generative AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) @@ -225,7 +216,7 @@ Microsoft में Azure क्लाउड एडवोकेट्स एक --- -### कोर शिक्षण +### कोर लर्निंग [![ML for Beginners](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) [![Data Science for Beginners](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) [![AI for Beginners](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) @@ -236,7 +227,7 @@ Microsoft में Azure क्लाउड एडवोकेट्स एक --- -### कोपिलट श्रृंखला +### कॉपिलट सीरीज़ [![Copilot for AI Paired Programming](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) [![Copilot for C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) [![Copilot Adventure](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) @@ -244,13 +235,13 @@ Microsoft में Azure क्लाउड एडवोकेट्स एक ## सहायता प्राप्त करना -**समस्याओं का सामना कर रहे हैं?** सामान्य समस्याओं के समाधान के लिए हमारी [समस्या निवारण गाइड](TROUBLESHOOTING.md) देखें। +**समस्याओं का सामना कर रहे हैं?** सामान्य समस्याओं के समाधान के लिए हमारी [ट्रबलशूटिंग गाइड](TROUBLESHOOTING.md) देखें। -यदि आप अटक गए हैं या AI ऐप बनाने के बारे में कोई प्रश्न है, तो MCP पर चर्चा में सीखने वालों और अनुभवी डेवलपर्स से जुड़ें। यह एक सहायक समुदाय है जहाँ प्रश्न स्वागत योग्य हैं और ज्ञान स्वतंत्र रूप से साझा किया जाता है। +यदि आप अटक जाते हैं या AI ऐप्स बनाने के बारे में कोई प्रश्न है। MCP के बारे में चर्चा में अन्य सीखने वालों और अनुभवी डेवलपर्स के साथ शामिल हों। यह एक सहायक समुदाय है जहाँ प्रश्न स्वागत योग्य होते हैं और ज्ञान स्वतंत्र रूप से साझा किया जाता है। [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -यदि आपके पास उत्पाद प्रतिक्रिया है या निर्माण के दौरान त्रुटियाँ हैं, तो यहाँ जाएँ: +यदि आपके पास उत्पाद प्रतिक्रिया या निर्माण के दौरान त्रुटियाँ हैं तो यहां जाएँ: [![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) @@ -258,5 +249,5 @@ Microsoft में Azure क्लाउड एडवोकेट्स एक **अस्वीकरण**: -यह दस्तावेज़ AI अनुवाद सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) का उपयोग करके अनुवादित किया गया है। जबकि हम सटीकता के लिए प्रयासरत हैं, कृपया ध्यान दें कि स्वचालित अनुवाद में त्रुटियाँ या असमानताएँ हो सकती हैं। मूल दस्तावेज़ अपनी मूल भाषा में ही प्राधिकृत स्रोत माना जाना चाहिए। महत्वपूर्ण जानकारी के लिए, पेशेवर मानव अनुवाद की सिफारिश की जाती है। इस अनुवाद के उपयोग से उत्पन्न किसी भी गलतफहमी या ग़लत व्याख्या के लिए हम जिम्मेदार नहीं हैं। +यह दस्तावेज़ एआई अनुवाद सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) का उपयोग करके अनुवादित किया गया है। जबकि हम सटीकता के लिए प्रयासरत हैं, कृपया ध्यान रखें कि स्वचालित अनुवाद में त्रुटियाँ या असामयिकताएँ हो सकती हैं। मूल दस्तावेज़ अपनी मूल भाषा में प्रमाणित स्रोत माना जाना चाहिए। महत्वपूर्ण जानकारी के लिए पेशेवर मानव अनुवाद की सिफारिश की जाती है। इस अनुवाद के उपयोग से उत्पन्न किसी भी गलतफहमी या गलत व्याख्या के लिए हम जिम्मेदार नहीं हैं। \ No newline at end of file diff --git a/translations/hi/SECURITY.md b/translations/hi/SECURITY.md index 44780fb5..e9e32924 100644 --- a/translations/hi/SECURITY.md +++ b/translations/hi/SECURITY.md @@ -1,12 +1,3 @@ - ## सुरक्षा Microsoft हमारे सॉफ़्टवेयर उत्पादों और सेवाओं की सुरक्षा को गंभीरता से लेता है, जिसमें हमारे GitHub संगठनों के माध्यम से प्रबंधित सभी स्रोत कोड रिपॉजिटरी शामिल हैं, जैसे [Microsoft](https://github.com/Microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet](https://github.com/aspnet), [Xamarin](https://github.com/xamarin), और [हमारे GitHub संगठन](https://opensource.microsoft.com/)। diff --git a/translations/hi/SUPPORT.md b/translations/hi/SUPPORT.md index 1a2f3a50..79ba7c68 100644 --- a/translations/hi/SUPPORT.md +++ b/translations/hi/SUPPORT.md @@ -1,12 +1,3 @@ - # समर्थन ## समस्याएँ दर्ज करने और सहायता प्राप्त करने का तरीका diff --git a/translations/hi/TROUBLESHOOTING.md b/translations/hi/TROUBLESHOOTING.md index abb5b427..d8b8787a 100644 --- a/translations/hi/TROUBLESHOOTING.md +++ b/translations/hi/TROUBLESHOOTING.md @@ -1,12 +1,3 @@ - # समस्या निवारण गाइड यह गाइड आपको Data Science for Beginners पाठ्यक्रम के दौरान आने वाली सामान्य समस्याओं के समाधान प्रदान करता है। diff --git a/translations/hi/USAGE.md b/translations/hi/USAGE.md index f8044543..77ddb47e 100644 --- a/translations/hi/USAGE.md +++ b/translations/hi/USAGE.md @@ -1,12 +1,3 @@ - # उपयोग गाइड यह गाइड शुरुआती डेटा साइंस पाठ्यक्रम का उपयोग करने के उदाहरण और सामान्य कार्यप्रवाह प्रदान करता है। diff --git a/translations/hi/docs/_sidebar.md b/translations/hi/docs/_sidebar.md index efbcd664..74253220 100644 --- a/translations/hi/docs/_sidebar.md +++ b/translations/hi/docs/_sidebar.md @@ -1,12 +1,3 @@ - - परिचय - [डेटा साइंस की परिभाषा](../1-Introduction/01-defining-data-science/README.md) - [डेटा साइंस के नैतिक पहलू](../1-Introduction/02-ethics/README.md) diff --git a/translations/hi/examples/README.md b/translations/hi/examples/README.md index c8e45f2a..24438e9f 100644 --- a/translations/hi/examples/README.md +++ b/translations/hi/examples/README.md @@ -1,12 +1,3 @@ - # शुरुआती लोगों के लिए डेटा साइंस के उदाहरण उदाहरण निर्देशिका में आपका स्वागत है! यह सरल और अच्छी तरह से टिप्पणी किए गए उदाहरणों का संग्रह आपको डेटा साइंस शुरू करने में मदद करने के लिए डिज़ाइन किया गया है, भले ही आप पूरी तरह से नए हों। diff --git a/translations/hi/for-teachers.md b/translations/hi/for-teachers.md index 5964aec8..231a7b27 100644 --- a/translations/hi/for-teachers.md +++ b/translations/hi/for-teachers.md @@ -1,12 +1,3 @@ - ## शिक्षकों के लिए क्या आप इस पाठ्यक्रम का उपयोग अपनी कक्षा में करना चाहेंगे? कृपया इसे स्वतंत्र रूप से उपयोग करें! diff --git a/translations/hi/quiz-app/README.md b/translations/hi/quiz-app/README.md index e13305e0..61681d8a 100644 --- a/translations/hi/quiz-app/README.md +++ b/translations/hi/quiz-app/README.md @@ -1,12 +1,3 @@ - # क्विज़ ये क्विज़ डेटा साइंस पाठ्यक्रम के लिए प्री- और पोस्ट-लेक्चर क्विज़ हैं, जो https://aka.ms/datascience-beginners पर उपलब्ध है। diff --git a/translations/hi/sketchnotes/README.md b/translations/hi/sketchnotes/README.md index 8744f8ce..54b5584a 100644 --- a/translations/hi/sketchnotes/README.md +++ b/translations/hi/sketchnotes/README.md @@ -1,12 +1,3 @@ - सभी स्केच नोट्स यहां देखें! ## क्रेडिट्स diff --git a/translations/ja/.co-op-translator.json b/translations/ja/.co-op-translator.json new file mode 100644 index 00000000..cc85023c --- /dev/null +++ b/translations/ja/.co-op-translator.json @@ -0,0 +1,422 @@ +{ + "1-Introduction/01-defining-data-science/README.md": { + "original_hash": "43212cc1ac137b7bb1dcfb37ca06b0f4", + "translation_date": "2025-10-25T18:41:49+00:00", + "source_file": "1-Introduction/01-defining-data-science/README.md", + "language_code": "ja" + }, + "1-Introduction/01-defining-data-science/assignment.md": { + "original_hash": "4e0f1773b9bee1be3b28f9fe2c71b3de", + "translation_date": "2025-08-25T16:56:42+00:00", + "source_file": "1-Introduction/01-defining-data-science/assignment.md", + "language_code": "ja" + }, + "1-Introduction/01-defining-data-science/solution/assignment.md": { + "original_hash": "a8f79b9c0484c35b4f26e8aec7fc4d56", + "translation_date": "2025-08-25T16:57:47+00:00", + "source_file": 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b/translations/ja/1-Introduction/01-defining-data-science/assignment.md index a2d5ff8a..58cd24c9 100644 --- a/translations/ja/1-Introduction/01-defining-data-science/assignment.md +++ b/translations/ja/1-Introduction/01-defining-data-science/assignment.md @@ -1,12 +1,3 @@ - # 課題: データサイエンスのシナリオ この最初の課題では、現実のプロセスや問題について考え、それをデータサイエンスのプロセスを使ってどのように改善できるかを考えてもらいます。以下の点について考えてみてください： diff --git a/translations/ja/1-Introduction/01-defining-data-science/solution/assignment.md b/translations/ja/1-Introduction/01-defining-data-science/solution/assignment.md index 378a390e..5a0fcffd 100644 --- a/translations/ja/1-Introduction/01-defining-data-science/solution/assignment.md +++ b/translations/ja/1-Introduction/01-defining-data-science/solution/assignment.md @@ -1,12 +1,3 @@ - # 課題: データサイエンスのシナリオ この最初の課題では、現実のプロセスや問題について考え、それをデータサイエンスのプロセスを使ってどのように改善できるかを考えてもらいます。以下の点について考えてみてください： diff --git a/translations/ja/1-Introduction/02-ethics/README.md b/translations/ja/1-Introduction/02-ethics/README.md index 1f89ba6f..f1819346 100644 --- a/translations/ja/1-Introduction/02-ethics/README.md +++ b/translations/ja/1-Introduction/02-ethics/README.md @@ -1,12 +1,3 @@ - # データ倫理の概要 |![ スケッチノート by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/02-Ethics.png)| diff --git a/translations/ja/1-Introduction/02-ethics/assignment.md b/translations/ja/1-Introduction/02-ethics/assignment.md index f0e6dc54..0020198a 100644 --- a/translations/ja/1-Introduction/02-ethics/assignment.md +++ b/translations/ja/1-Introduction/02-ethics/assignment.md @@ -1,12 +1,3 @@ - ## データ倫理のケーススタディを書く ## 指示 diff --git a/translations/ja/1-Introduction/03-defining-data/README.md b/translations/ja/1-Introduction/03-defining-data/README.md index a304ee14..8cebb7e0 100644 --- a/translations/ja/1-Introduction/03-defining-data/README.md +++ b/translations/ja/1-Introduction/03-defining-data/README.md @@ -1,12 +1,3 @@ - # データの定義 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/03-DefiningData.png)| diff --git a/translations/ja/1-Introduction/03-defining-data/assignment.md b/translations/ja/1-Introduction/03-defining-data/assignment.md index e919af2c..1c69d47b 100644 --- a/translations/ja/1-Introduction/03-defining-data/assignment.md +++ b/translations/ja/1-Introduction/03-defining-data/assignment.md @@ -1,12 +1,3 @@ - # データセットの分類 ## 指示 diff --git a/translations/ja/1-Introduction/04-stats-and-probability/README.md b/translations/ja/1-Introduction/04-stats-and-probability/README.md index 07793be6..a1350db1 100644 --- a/translations/ja/1-Introduction/04-stats-and-probability/README.md +++ b/translations/ja/1-Introduction/04-stats-and-probability/README.md @@ -1,12 +1,3 @@ - # 統計学と確率論の簡単な紹介 |![ スケッチノート by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/04-Statistics-Probability.png)| @@ -64,7 +55,7 @@ CO_OP_TRANSLATOR_METADATA: 中央値と四分位数の関係を図示するために、**箱ひげ図**と呼ばれる図を使用します： -箱ひげ図の説明 +箱ひげ図の説明 ここでは**四分位範囲**IQR=Q3-Q1を計算し、**外れ値**と呼ばれる値を特定します。これらは[Q1-1.5*IQR,Q3+1.5*IQR]の範囲外にある値です。 diff --git a/translations/ja/1-Introduction/04-stats-and-probability/assignment.md b/translations/ja/1-Introduction/04-stats-and-probability/assignment.md index 0d4bcecc..b513307f 100644 --- a/translations/ja/1-Introduction/04-stats-and-probability/assignment.md +++ b/translations/ja/1-Introduction/04-stats-and-probability/assignment.md @@ -1,12 +1,3 @@ - # 小規模な糖尿病研究 この課題では、[こちら](https://www4.stat.ncsu.edu/~boos/var.select/diabetes.html)から取得した糖尿病患者の小規模なデータセットを使用します。 diff --git a/translations/ja/1-Introduction/README.md b/translations/ja/1-Introduction/README.md index d26c2721..479d1153 100644 --- a/translations/ja/1-Introduction/README.md +++ b/translations/ja/1-Introduction/README.md @@ -1,12 +1,3 @@ - # データサイエンス入門 ![データの活用](../../../translated_images/ja/data.48e22bb7617d8d92188afbc4c48effb920ba79f5cebdc0652cd9f34bbbd90c18.jpg) diff --git a/translations/ja/2-Working-With-Data/05-relational-databases/README.md b/translations/ja/2-Working-With-Data/05-relational-databases/README.md index 8b83052d..16df7c26 100644 --- a/translations/ja/2-Working-With-Data/05-relational-databases/README.md +++ b/translations/ja/2-Working-With-Data/05-relational-databases/README.md @@ -1,12 +1,3 @@ - # データ操作：リレーショナルデータベース |![ スケッチノート by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/05-RelationalData.png)| diff --git a/translations/ja/2-Working-With-Data/05-relational-databases/assignment.md b/translations/ja/2-Working-With-Data/05-relational-databases/assignment.md index c4b52ca8..2c511abe 100644 --- a/translations/ja/2-Working-With-Data/05-relational-databases/assignment.md +++ b/translations/ja/2-Working-With-Data/05-relational-databases/assignment.md @@ -1,12 +1,3 @@ - # 空港データの表示 [SQLite](https://sqlite.org/index.html)を基盤とした[データベース](https://raw.githubusercontent.com/Microsoft/Data-Science-For-Beginners/main/2-Working-With-Data/05-relational-databases/airports.db)が提供されています。このデータベースには空港に関する情報が含まれています。以下にスキーマが表示されています。[Visual Studio Code](https://code.visualstudio.com?WT.mc_id=academic-77958-bethanycheum)の[SQLite拡張機能](https://marketplace.visualstudio.com/items?itemName=alexcvzz.vscode-sqlite&WT.mc_id=academic-77958-bethanycheum)を使用して、さまざまな都市の空港情報を表示します。 diff --git a/translations/ja/2-Working-With-Data/06-non-relational/README.md b/translations/ja/2-Working-With-Data/06-non-relational/README.md index 7ae838ae..8c3a27e2 100644 --- a/translations/ja/2-Working-With-Data/06-non-relational/README.md +++ b/translations/ja/2-Working-With-Data/06-non-relational/README.md @@ -1,12 +1,3 @@ - # データの操作: 非リレーショナルデータ |![ スケッチノート by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/06-NoSQL.png)| diff --git a/translations/ja/2-Working-With-Data/06-non-relational/assignment.md b/translations/ja/2-Working-With-Data/06-non-relational/assignment.md index b6661ed6..d95d54bb 100644 --- a/translations/ja/2-Working-With-Data/06-non-relational/assignment.md +++ b/translations/ja/2-Working-With-Data/06-non-relational/assignment.md @@ -1,12 +1,3 @@ - # ソーダの利益 ## 指示 diff --git a/translations/ja/2-Working-With-Data/07-python/README.md b/translations/ja/2-Working-With-Data/07-python/README.md index 71a6ea80..8d421987 100644 --- a/translations/ja/2-Working-With-Data/07-python/README.md +++ b/translations/ja/2-Working-With-Data/07-python/README.md @@ -1,12 +1,3 @@ - # データの操作: PythonとPandasライブラリ | ![ [(@sketchthedocs)](https://sketchthedocs.dev) によるスケッチノート ](../../sketchnotes/07-WorkWithPython.png) | diff --git a/translations/ja/2-Working-With-Data/07-python/assignment.md b/translations/ja/2-Working-With-Data/07-python/assignment.md index c571d647..3ed76be1 100644 --- a/translations/ja/2-Working-With-Data/07-python/assignment.md +++ b/translations/ja/2-Working-With-Data/07-python/assignment.md @@ -1,12 +1,3 @@ - # Pythonによるデータ処理課題 この課題では、これまでのチャレンジで開発を始めたコードをさらに詳しく説明していただきます。課題は以下の2つの部分で構成されています。 diff --git a/translations/ja/2-Working-With-Data/08-data-preparation/README.md b/translations/ja/2-Working-With-Data/08-data-preparation/README.md index f30b1e2e..55620bdd 100644 --- a/translations/ja/2-Working-With-Data/08-data-preparation/README.md +++ b/translations/ja/2-Working-With-Data/08-data-preparation/README.md @@ -1,12 +1,3 @@ - # データの取り扱い: データ準備 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/08-DataPreparation.png)| diff --git a/translations/ja/2-Working-With-Data/08-data-preparation/assignment.md b/translations/ja/2-Working-With-Data/08-data-preparation/assignment.md index b8a5bf51..7552afe5 100644 --- a/translations/ja/2-Working-With-Data/08-data-preparation/assignment.md +++ b/translations/ja/2-Working-With-Data/08-data-preparation/assignment.md @@ -1,12 +1,3 @@ - # フォームからのデータ評価 クライアントは、顧客層に関する基本的なデータを収集するための[小さなフォーム](../../../../2-Working-With-Data/08-data-preparation/index.html)をテストしてきました。彼らは収集したデータを検証するためにその結果を持ってきました。ブラウザで`index.html`ページを開いてフォームを確認することができます。 diff --git a/translations/ja/2-Working-With-Data/README.md b/translations/ja/2-Working-With-Data/README.md index 7cf40c8e..2f5dd9bc 100644 --- a/translations/ja/2-Working-With-Data/README.md +++ b/translations/ja/2-Working-With-Data/README.md @@ -1,12 +1,3 @@ - # データの活用 ![data love](../../../translated_images/ja/data-love.a22ef29e6742c852505ada062920956d3d7604870b281a8ca7c7ac6f37381d5a.jpg) diff --git a/translations/ja/3-Data-Visualization/09-visualization-quantities/README.md b/translations/ja/3-Data-Visualization/09-visualization-quantities/README.md index 9d10edc7..bc2de120 100644 --- a/translations/ja/3-Data-Visualization/09-visualization-quantities/README.md +++ b/translations/ja/3-Data-Visualization/09-visualization-quantities/README.md @@ -1,12 +1,3 @@ - # 数量の可視化 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/09-Visualizing-Quantities.png)| diff --git a/translations/ja/3-Data-Visualization/09-visualization-quantities/assignment.md b/translations/ja/3-Data-Visualization/09-visualization-quantities/assignment.md index 7180575b..1ebe0e17 100644 --- a/translations/ja/3-Data-Visualization/09-visualization-quantities/assignment.md +++ b/translations/ja/3-Data-Visualization/09-visualization-quantities/assignment.md @@ -1,12 +1,3 @@ - # 線グラフ、散布図、棒グラフ ## 手順 diff --git a/translations/ja/3-Data-Visualization/10-visualization-distributions/README.md b/translations/ja/3-Data-Visualization/10-visualization-distributions/README.md index bffa2604..7863bba0 100644 --- a/translations/ja/3-Data-Visualization/10-visualization-distributions/README.md +++ b/translations/ja/3-Data-Visualization/10-visualization-distributions/README.md @@ -1,12 +1,3 @@ - # 分布の可視化 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/10-Visualizing-Distributions.png)| diff --git a/translations/ja/3-Data-Visualization/10-visualization-distributions/assignment.md b/translations/ja/3-Data-Visualization/10-visualization-distributions/assignment.md index 0b5130ea..6ea8f575 100644 --- a/translations/ja/3-Data-Visualization/10-visualization-distributions/assignment.md +++ b/translations/ja/3-Data-Visualization/10-visualization-distributions/assignment.md @@ -1,12 +1,3 @@ - # スキルを活用しよう ## 手順 diff --git a/translations/ja/3-Data-Visualization/11-visualization-proportions/README.md b/translations/ja/3-Data-Visualization/11-visualization-proportions/README.md index 63b710cb..d32ae1d3 100644 --- a/translations/ja/3-Data-Visualization/11-visualization-proportions/README.md +++ b/translations/ja/3-Data-Visualization/11-visualization-proportions/README.md @@ -1,12 +1,3 @@ - # 比率の可視化 |![ [(@sketchthedocs)](https://sketchthedocs.dev) によるスケッチノート ](../../sketchnotes/11-Visualizing-Proportions.png)| diff --git a/translations/ja/3-Data-Visualization/11-visualization-proportions/assignment.md b/translations/ja/3-Data-Visualization/11-visualization-proportions/assignment.md index cf2d10ac..ab0e2b87 100644 --- a/translations/ja/3-Data-Visualization/11-visualization-proportions/assignment.md +++ b/translations/ja/3-Data-Visualization/11-visualization-proportions/assignment.md @@ -1,12 +1,3 @@ - # Excelで試してみよう ## 手順 diff --git a/translations/ja/3-Data-Visualization/12-visualization-relationships/README.md b/translations/ja/3-Data-Visualization/12-visualization-relationships/README.md index 52900b10..8ae69716 100644 --- a/translations/ja/3-Data-Visualization/12-visualization-relationships/README.md +++ b/translations/ja/3-Data-Visualization/12-visualization-relationships/README.md @@ -1,12 +1,3 @@ - # 関係の可視化: ハチミツについて 🍯 |![ [(@sketchthedocs)](https://sketchthedocs.dev) によるスケッチノート ](../../sketchnotes/12-Visualizing-Relationships.png)| diff --git a/translations/ja/3-Data-Visualization/12-visualization-relationships/assignment.md b/translations/ja/3-Data-Visualization/12-visualization-relationships/assignment.md index b8db0039..b7dc1a60 100644 --- a/translations/ja/3-Data-Visualization/12-visualization-relationships/assignment.md +++ b/translations/ja/3-Data-Visualization/12-visualization-relationships/assignment.md @@ -1,12 +1,3 @@ - # 蜂の巣を探る ## 手順 diff --git a/translations/ja/3-Data-Visualization/13-meaningful-visualizations/README.md b/translations/ja/3-Data-Visualization/13-meaningful-visualizations/README.md index 4424cc7a..4aa6c586 100644 --- a/translations/ja/3-Data-Visualization/13-meaningful-visualizations/README.md +++ b/translations/ja/3-Data-Visualization/13-meaningful-visualizations/README.md @@ -1,12 +1,3 @@ - # 意味のあるデータビジュアライゼーションを作る |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/13-MeaningfulViz.png)| diff --git a/translations/ja/3-Data-Visualization/13-meaningful-visualizations/assignment.md b/translations/ja/3-Data-Visualization/13-meaningful-visualizations/assignment.md index 615f1616..cd82b3a3 100644 --- a/translations/ja/3-Data-Visualization/13-meaningful-visualizations/assignment.md +++ b/translations/ja/3-Data-Visualization/13-meaningful-visualizations/assignment.md @@ -1,12 +1,3 @@ - # 独自のカスタムビジュアルを作成しよう ## 手順 diff --git a/translations/ja/3-Data-Visualization/13-meaningful-visualizations/solution/README.md b/translations/ja/3-Data-Visualization/13-meaningful-visualizations/solution/README.md index 23f035b0..73d79fa7 100644 --- a/translations/ja/3-Data-Visualization/13-meaningful-visualizations/solution/README.md +++ b/translations/ja/3-Data-Visualization/13-meaningful-visualizations/solution/README.md @@ -1,12 +1,3 @@ - # 危険な関係 データビジュアライゼーションプロジェクト 始めるには、マシンにNPMとNodeがインストールされていることを確認してください。依存関係をインストール（npm install）し、プロジェクトをローカルで実行します（npm run serve）: diff --git a/translations/ja/3-Data-Visualization/13-meaningful-visualizations/starter/README.md b/translations/ja/3-Data-Visualization/13-meaningful-visualizations/starter/README.md index 5efb6b74..2fe1204d 100644 --- a/translations/ja/3-Data-Visualization/13-meaningful-visualizations/starter/README.md +++ b/translations/ja/3-Data-Visualization/13-meaningful-visualizations/starter/README.md @@ -1,12 +1,3 @@ - # 危険な関係 データビジュアライゼーションプロジェクト 始めるには、マシンにNPMとNodeがインストールされていることを確認してください。依存関係をインストール（npm install）し、その後プロジェクトをローカルで実行してください（npm run serve）: diff --git a/translations/ja/3-Data-Visualization/R/09-visualization-quantities/README.md b/translations/ja/3-Data-Visualization/R/09-visualization-quantities/README.md index f509cb48..02ac1831 100644 --- a/translations/ja/3-Data-Visualization/R/09-visualization-quantities/README.md +++ b/translations/ja/3-Data-Visualization/R/09-visualization-quantities/README.md @@ -1,12 +1,3 @@ - # 量を視覚化する |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/sketchnotes/09-Visualizing-Quantities.png)| |:---:| diff --git a/translations/ja/3-Data-Visualization/R/09-visualization-quantities/assignment.md b/translations/ja/3-Data-Visualization/R/09-visualization-quantities/assignment.md index 1416eeb0..8bee3e0f 100644 --- a/translations/ja/3-Data-Visualization/R/09-visualization-quantities/assignment.md +++ b/translations/ja/3-Data-Visualization/R/09-visualization-quantities/assignment.md @@ -1,12 +1,3 @@ - # 線グラフ、散布図、棒グラフ ## 課題 diff --git a/translations/ja/3-Data-Visualization/R/10-visualization-distributions/README.md b/translations/ja/3-Data-Visualization/R/10-visualization-distributions/README.md index d06736cd..f693d045 100644 --- a/translations/ja/3-Data-Visualization/R/10-visualization-distributions/README.md +++ b/translations/ja/3-Data-Visualization/R/10-visualization-distributions/README.md @@ -1,12 +1,3 @@ - # 分布の可視化 |![ スケッチノート by [(@sketchthedocs)](https://sketchthedocs.dev) ](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/sketchnotes/10-Visualizing-Distributions.png)| diff --git a/translations/ja/3-Data-Visualization/R/10-visualization-distributions/assignment.md b/translations/ja/3-Data-Visualization/R/10-visualization-distributions/assignment.md index 563f32bd..c51ea05c 100644 --- a/translations/ja/3-Data-Visualization/R/10-visualization-distributions/assignment.md +++ b/translations/ja/3-Data-Visualization/R/10-visualization-distributions/assignment.md @@ -1,12 +1,3 @@ - # スキルを活用しよう ## 手順 diff --git a/translations/ja/3-Data-Visualization/R/11-visualization-proportions/README.md b/translations/ja/3-Data-Visualization/R/11-visualization-proportions/README.md index dffa111d..e7eb8ade 100644 --- a/translations/ja/3-Data-Visualization/R/11-visualization-proportions/README.md +++ b/translations/ja/3-Data-Visualization/R/11-visualization-proportions/README.md @@ -1,12 +1,3 @@ - # 比率の可視化 |![ [(@sketchthedocs)](https://sketchthedocs.dev) によるスケッチノート ](../../../sketchnotes/11-Visualizing-Proportions.png)| diff --git a/translations/ja/3-Data-Visualization/R/12-visualization-relationships/README.md b/translations/ja/3-Data-Visualization/R/12-visualization-relationships/README.md index 61f5efc5..5723e3fc 100644 --- a/translations/ja/3-Data-Visualization/R/12-visualization-relationships/README.md +++ b/translations/ja/3-Data-Visualization/R/12-visualization-relationships/README.md @@ -1,12 +1,3 @@ - # 関係の可視化: ハチミツについて 🍯 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../../sketchnotes/12-Visualizing-Relationships.png)| diff --git a/translations/ja/3-Data-Visualization/R/13-meaningful-vizualizations/README.md b/translations/ja/3-Data-Visualization/R/13-meaningful-vizualizations/README.md index 1960c196..cb703e81 100644 --- a/translations/ja/3-Data-Visualization/R/13-meaningful-vizualizations/README.md +++ b/translations/ja/3-Data-Visualization/R/13-meaningful-vizualizations/README.md @@ -1,12 +1,3 @@ - # 意味のあるデータビジュアライゼーションを作る |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../../sketchnotes/13-MeaningfulViz.png)| diff --git a/translations/ja/3-Data-Visualization/README.md b/translations/ja/3-Data-Visualization/README.md index dc85a519..11701aa1 100644 --- a/translations/ja/3-Data-Visualization/README.md +++ b/translations/ja/3-Data-Visualization/README.md @@ -1,12 +1,3 @@ - # ビジュアライゼーション ![ラベンダーの花にとまるミツバチ](../../../translated_images/ja/bee.0aa1d91132b12e3a8994b9ca12816d05ce1642010d9b8be37f8d37365ba845cf.jpg) diff --git a/translations/ja/4-Data-Science-Lifecycle/14-Introduction/README.md b/translations/ja/4-Data-Science-Lifecycle/14-Introduction/README.md index 722c04b7..835c0189 100644 --- a/translations/ja/4-Data-Science-Lifecycle/14-Introduction/README.md +++ b/translations/ja/4-Data-Science-Lifecycle/14-Introduction/README.md @@ -1,12 +1,3 @@ - # データサイエンスライフサイクルの紹介 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/14-DataScience-Lifecycle.png)| diff --git a/translations/ja/4-Data-Science-Lifecycle/14-Introduction/assignment.md b/translations/ja/4-Data-Science-Lifecycle/14-Introduction/assignment.md index a4e1b42d..aa7d1fa0 100644 --- a/translations/ja/4-Data-Science-Lifecycle/14-Introduction/assignment.md +++ b/translations/ja/4-Data-Science-Lifecycle/14-Introduction/assignment.md @@ -1,12 +1,3 @@ - # データセットの評価 クライアントが、ニューヨーク市のタクシー利用者の季節ごとの支出傾向を調査するための支援を求めています。 diff --git a/translations/ja/4-Data-Science-Lifecycle/15-analyzing/README.md b/translations/ja/4-Data-Science-Lifecycle/15-analyzing/README.md index 16955e9f..dfe3823c 100644 --- a/translations/ja/4-Data-Science-Lifecycle/15-analyzing/README.md +++ b/translations/ja/4-Data-Science-Lifecycle/15-analyzing/README.md @@ -1,12 +1,3 @@ - # データサイエンスライフサイクル: 分析 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/15-Analyzing.png)| diff --git a/translations/ja/4-Data-Science-Lifecycle/15-analyzing/assignment.md b/translations/ja/4-Data-Science-Lifecycle/15-analyzing/assignment.md index d4a4fecb..d12bcfc7 100644 --- a/translations/ja/4-Data-Science-Lifecycle/15-analyzing/assignment.md +++ b/translations/ja/4-Data-Science-Lifecycle/15-analyzing/assignment.md @@ -1,12 +1,3 @@ - # 答えを探る これは前回のレッスンの[課題](../14-Introduction/assignment.md)の続きで、データセットを簡単に見たところから始まります。今回はデータをさらに深く掘り下げていきます。 diff --git a/translations/ja/4-Data-Science-Lifecycle/16-communication/README.md b/translations/ja/4-Data-Science-Lifecycle/16-communication/README.md index cf5a877b..dc9dc9e8 100644 --- a/translations/ja/4-Data-Science-Lifecycle/16-communication/README.md +++ b/translations/ja/4-Data-Science-Lifecycle/16-communication/README.md @@ -1,12 +1,3 @@ - # データサイエンスライフサイクル: コミュニケーション |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev)](../../sketchnotes/16-Communicating.png)| diff --git a/translations/ja/4-Data-Science-Lifecycle/16-communication/assignment.md b/translations/ja/4-Data-Science-Lifecycle/16-communication/assignment.md index 3bdc4d61..9e83f2cb 100644 --- a/translations/ja/4-Data-Science-Lifecycle/16-communication/assignment.md +++ b/translations/ja/4-Data-Science-Lifecycle/16-communication/assignment.md @@ -1,12 +1,3 @@ - # 物語を語る ## 指示 diff --git a/translations/ja/4-Data-Science-Lifecycle/README.md b/translations/ja/4-Data-Science-Lifecycle/README.md index 64d85c8a..3f827cba 100644 --- a/translations/ja/4-Data-Science-Lifecycle/README.md +++ b/translations/ja/4-Data-Science-Lifecycle/README.md @@ -1,12 +1,3 @@ - # データサイエンスライフサイクル ![communication](../../../translated_images/ja/communication.06d8e2a88d30d168d661ad9f9f0a4f947ebff3719719cfdaf9ed00a406a01ead.jpg) diff --git a/translations/ja/5-Data-Science-In-Cloud/17-Introduction/README.md b/translations/ja/5-Data-Science-In-Cloud/17-Introduction/README.md index 0e0a45a0..ef753790 100644 --- a/translations/ja/5-Data-Science-In-Cloud/17-Introduction/README.md +++ b/translations/ja/5-Data-Science-In-Cloud/17-Introduction/README.md @@ -1,12 +1,3 @@ - # クラウドにおけるデータサイエンス入門 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/17-DataScience-Cloud.png)| diff --git a/translations/ja/5-Data-Science-In-Cloud/17-Introduction/assignment.md b/translations/ja/5-Data-Science-In-Cloud/17-Introduction/assignment.md index 56de6198..bfb3a70e 100644 --- a/translations/ja/5-Data-Science-In-Cloud/17-Introduction/assignment.md +++ b/translations/ja/5-Data-Science-In-Cloud/17-Introduction/assignment.md @@ -1,12 +1,3 @@ - # 市場調査 ## 指示 diff --git a/translations/ja/5-Data-Science-In-Cloud/18-Low-Code/README.md b/translations/ja/5-Data-Science-In-Cloud/18-Low-Code/README.md index 78806e9f..43b6d6ab 100644 --- a/translations/ja/5-Data-Science-In-Cloud/18-Low-Code/README.md +++ b/translations/ja/5-Data-Science-In-Cloud/18-Low-Code/README.md @@ -1,12 +1,3 @@ - # クラウドでのデータサイエンス: 「ローコード/ノーコード」アプローチ |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/18-DataScience-Cloud.png)| diff --git a/translations/ja/5-Data-Science-In-Cloud/18-Low-Code/assignment.md b/translations/ja/5-Data-Science-In-Cloud/18-Low-Code/assignment.md index b1e499d4..18ba1c89 100644 --- a/translations/ja/5-Data-Science-In-Cloud/18-Low-Code/assignment.md +++ b/translations/ja/5-Data-Science-In-Cloud/18-Low-Code/assignment.md @@ -1,12 +1,3 @@ - # Azure MLでのローコード/ノーコード データサイエンスプロジェクト ## 手順 diff --git a/translations/ja/5-Data-Science-In-Cloud/19-Azure/README.md b/translations/ja/5-Data-Science-In-Cloud/19-Azure/README.md index 29e2c9b8..a215bbc1 100644 --- a/translations/ja/5-Data-Science-In-Cloud/19-Azure/README.md +++ b/translations/ja/5-Data-Science-In-Cloud/19-Azure/README.md @@ -1,12 +1,3 @@ - # クラウドでのデータサイエンス: "Azure ML SDK" の方法 |![ [(@sketchthedocs)](https://sketchthedocs.dev) によるスケッチノート](../../sketchnotes/19-DataScience-Cloud.png)| diff --git a/translations/ja/5-Data-Science-In-Cloud/19-Azure/assignment.md b/translations/ja/5-Data-Science-In-Cloud/19-Azure/assignment.md index b08fbcf1..a4648d38 100644 --- a/translations/ja/5-Data-Science-In-Cloud/19-Azure/assignment.md +++ b/translations/ja/5-Data-Science-In-Cloud/19-Azure/assignment.md @@ -1,12 +1,3 @@ - # Azure ML SDK を使用したデータサイエンスプロジェクト ## 手順 diff --git a/translations/ja/5-Data-Science-In-Cloud/README.md b/translations/ja/5-Data-Science-In-Cloud/README.md index c789e8e6..acd1fa03 100644 --- a/translations/ja/5-Data-Science-In-Cloud/README.md +++ b/translations/ja/5-Data-Science-In-Cloud/README.md @@ -1,12 +1,3 @@ - # クラウドでのデータサイエンス ![cloud-picture](../../../translated_images/ja/cloud-picture.f5526de3c6c6387b2d656ba94f019b3352e5e3854a78440e4fb00c93e2dea675.jpg) diff --git a/translations/ja/6-Data-Science-In-Wild/20-Real-World-Examples/README.md b/translations/ja/6-Data-Science-In-Wild/20-Real-World-Examples/README.md index 880ecb6b..9ca7b1ad 100644 --- a/translations/ja/6-Data-Science-In-Wild/20-Real-World-Examples/README.md +++ b/translations/ja/6-Data-Science-In-Wild/20-Real-World-Examples/README.md @@ -1,12 +1,3 @@ - # 現実世界のデータサイエンス | ![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/20-DataScience-RealWorld.png) | diff --git a/translations/ja/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md b/translations/ja/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md index 02946cef..8b772d26 100644 --- a/translations/ja/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md +++ b/translations/ja/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md @@ -1,12 +1,3 @@ - # 惑星コンピューターのデータセットを探る ## 手順 diff --git a/translations/ja/6-Data-Science-In-Wild/README.md b/translations/ja/6-Data-Science-In-Wild/README.md index 7b9293a7..359d891d 100644 --- a/translations/ja/6-Data-Science-In-Wild/README.md +++ b/translations/ja/6-Data-Science-In-Wild/README.md @@ -1,12 +1,3 @@ - # 実社会でのデータサイエンス 業界全体におけるデータサイエンスの実際の応用例。 diff --git a/translations/ja/AGENTS.md b/translations/ja/AGENTS.md index 05550959..907fcd75 100644 --- a/translations/ja/AGENTS.md +++ b/translations/ja/AGENTS.md @@ -1,12 +1,3 @@ - # AGENTS.md ## プロジェクト概要 diff --git a/translations/ja/CODE_OF_CONDUCT.md b/translations/ja/CODE_OF_CONDUCT.md index ad2ba015..40c71ca5 100644 --- a/translations/ja/CODE_OF_CONDUCT.md +++ b/translations/ja/CODE_OF_CONDUCT.md @@ -1,12 +1,3 @@ - # マイクロソフト オープンソース行動規範 このプロジェクトは、[マイクロソフト オープンソース行動規範](https://opensource.microsoft.com/codeofconduct/)を採用しています。 diff --git a/translations/ja/CONTRIBUTING.md b/translations/ja/CONTRIBUTING.md index dfa6ffb2..67bb71ee 100644 --- a/translations/ja/CONTRIBUTING.md +++ b/translations/ja/CONTRIBUTING.md @@ -1,12 +1,3 @@ - # 初心者向けデータサイエンスへの貢献 初心者向けデータサイエンスカリキュラムへの貢献に興味を持っていただきありがとうございます！コミュニティからの貢献を歓迎します。 diff --git a/translations/ja/INSTALLATION.md b/translations/ja/INSTALLATION.md index fff70218..ebd9ead9 100644 --- a/translations/ja/INSTALLATION.md +++ b/translations/ja/INSTALLATION.md @@ -1,12 +1,3 @@ - # インストールガイド このガイドでは、Data Science for Beginners カリキュラムを使用するための環境設定方法を説明します。 diff --git a/translations/ja/README.md b/translations/ja/README.md index 538bb8b8..d52dcaa0 100644 --- a/translations/ja/README.md +++ b/translations/ja/README.md @@ -1,13 +1,4 @@ - -# データサイエンス入門 - カリキュラム +# 初心者のためのデータサイエンス - カリキュラム [![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://github.com/codespaces/new?hide_repo_select=true&ref=main&repo=344191198) @@ -26,180 +17,183 @@ CO_OP_TRANSLATOR_METADATA: [![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) -マイクロソフトのAzure Cloud Advocatesは、データサイエンスに関する10週間、全20レッスンのカリキュラムを提供しています。各レッスンには、事前・事後のクイズ、レッスンを完了するための文章による指示、解答例、課題が含まれています。プロジェクトベースの教授法により、学びながら実践でき、新しいスキルを確実に身につけることができます。 +MicrosoftのAzure Cloud Advocatesは、データサイエンスに関する全10週間、20レッスンのカリキュラムを提供しています。各レッスンには、レッスン前とレッスン後のクイズ、レッスンを完了するための文書化された指示、解答例、および課題が含まれています。プロジェクトベースの教授法により、実際に作りながら学ぶことで、新しいスキルが「定着」しやすくなります。 -**著者の皆様に心からの感謝を：** [Jasmine Greenaway](https://www.twitter.com/paladique), [Dmitry Soshnikov](http://soshnikov.com), [Nitya Narasimhan](https://twitter.com/nitya), [Jalen McGee](https://twitter.com/JalenMcG), [Jen Looper](https://twitter.com/jenlooper), [Maud Levy](https://twitter.com/maudstweets), [Tiffany Souterre](https://twitter.com/TiffanySouterre), [Christopher Harrison](https://www.twitter.com/geektrainer)。 +**著者の皆様に心より感謝いたします:** [Jasmine Greenaway](https://www.twitter.com/paladique)、[Dmitry Soshnikov](http://soshnikov.com)、[Nitya Narasimhan](https://twitter.com/nitya)、[Jalen McGee](https://twitter.com/JalenMcG)、[Jen Looper](https://twitter.com/jenlooper)、[Maud Levy](https://twitter.com/maudstweets)、[Tiffany Souterre](https://twitter.com/TiffanySouterre)、[Christopher Harrison](https://www.twitter.com/geektrainer)。 -**🙏 特別な感謝を [Microsoft Student Ambassador](https://studentambassadors.microsoft.com/) の著者、レビュアー、コンテンツ貢献者の皆様へ🙏**、特に Aaryan Arora、[Aditya Garg](https://github.com/AdityaGarg00)、[Alondra Sanchez](https://www.linkedin.com/in/alondra-sanchez-molina/)、[Ankita Singh](https://www.linkedin.com/in/ankitasingh007)、[Anupam Mishra](https://www.linkedin.com/in/anupam--mishra/)、[Arpita Das](https://www.linkedin.com/in/arpitadas01/)、ChhailBihari Dubey、[Dibri Nsofor](https://www.linkedin.com/in/dibrinsofor)、[Dishita Bhasin](https://www.linkedin.com/in/dishita-bhasin-7065281bb)、[Majd Safi](https://www.linkedin.com/in/majd-s/)、[Max Blum](https://www.linkedin.com/in/max-blum-6036a1186/)、[Miguel Correa](https://www.linkedin.com/in/miguelmque/)、[Mohamma Iftekher (Iftu) Ebne Jalal](https://twitter.com/iftu119)、[Nawrin Tabassum](https://www.linkedin.com/in/nawrin-tabassum)、[Raymond Wangsa Putra](https://www.linkedin.com/in/raymond-wp/)、[Rohit Yadav](https://www.linkedin.com/in/rty2423)、Samridhi Sharma、[Sanya Sinha](https://www.linkedin.com/mwlite/in/sanya-sinha-13aab1200)、[Sheena Narula](https://www.linkedin.com/in/sheena-narua-n/)、[Tauqeer Ahmad](https://www.linkedin.com/in/tauqeerahmad5201/)、Yogendrasingh Pawar、[Vidushi Gupta](https://www.linkedin.com/in/vidushi-gupta07/)、[Jasleen Sondhi](https://www.linkedin.com/in/jasleen-sondhi/) +**🙏 特別な感謝を [Microsoft Student Ambassador](https://studentambassadors.microsoft.com/) の著者、レビュアー、コンテンツ提供者の皆様に🙏** 特にAaryan Arora、[Aditya Garg](https://github.com/AdityaGarg00)、[Alondra Sanchez](https://www.linkedin.com/in/alondra-sanchez-molina/)、[Ankita Singh](https://www.linkedin.com/in/ankitasingh007)、[Anupam Mishra](https://www.linkedin.com/in/anupam--mishra/)、[Arpita Das](https://www.linkedin.com/in/arpitadas01/)、ChhailBihari Dubey、[Dibri Nsofor](https://www.linkedin.com/in/dibrinsofor)、[Dishita Bhasin](https://www.linkedin.com/in/dishita-bhasin-7065281bb)、[Majd Safi](https://www.linkedin.com/in/majd-s/)、[Max Blum](https://www.linkedin.com/in/max-blum-6036a1186/)、[Miguel Correa](https://www.linkedin.com/in/miguelmque/)、[Mohamma Iftekher (Iftu) Ebne Jalal](https://twitter.com/iftu119)、[Nawrin Tabassum](https://www.linkedin.com/in/nawrin-tabassum)、[Raymond Wangsa Putra](https://www.linkedin.com/in/raymond-wp/)、[Rohit Yadav](https://www.linkedin.com/in/rty2423)、Samridhi Sharma、[Sanya Sinha](https://www.linkedin.com/mwlite/in/sanya-sinha-13aab1200)、[Sheena Narula](https://www.linkedin.com/in/sheena-narua-n/)、[Tauqeer Ahmad](https://www.linkedin.com/in/tauqeerahmad5201/)、Yogendrasingh Pawar、[Vidushi Gupta](https://www.linkedin.com/in/vidushi-gupta07/)、[Jasleen Sondhi](https://www.linkedin.com/in/jasleen-sondhi/) -|![Sketchnote by @sketchthedocs https://sketchthedocs.dev](../../../../translated_images/ja/00-Title.8af36cd35da1ac55.webp)| +|![Sketchnote by @sketchthedocs https://sketchthedocs.dev](../../translated_images/ja/00-Title.8af36cd35da1ac55.webp)| |:---:| -| データサイエンス入門 - _スケッチノート：[@nitya](https://twitter.com/nitya)_ | +| 初心者のためのデータサイエンス - _スケッチノート by [@nitya](https://twitter.com/nitya)_ | ### 🌐 多言語サポート -#### GitHub Actionによるサポート（自動かつ常に最新） +#### GitHub Action によるサポート（自動化＆常に最新） -[Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](../hi/README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](./README.md) | [Kannada](../kn/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../br/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) +[Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh-CN/README.md) | [Chinese (Traditional, Hong Kong)](../zh-HK/README.md) | [Chinese (Traditional, Macau)](../zh-MO/README.md) | [Chinese (Traditional, Taiwan)](../zh-TW/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](../hi/README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](./README.md) | [Kannada](../kn/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../pt-BR/README.md) | [Portuguese (Portugal)](../pt-PT/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) -> **ローカルでのクローンを希望しますか？** +> **ローカルでクローンしたいですか？** -> このリポジトリには50以上の言語翻訳が含まれており、ダウンロードサイズが大きくなっています。翻訳を含めずクローンするには、sparse checkoutを使用してください： +> このリポジトリは50以上の言語翻訳を含んでおり、ダウンロードサイズが大きくなります。翻訳なしでクローンするにはスパースチェックアウトを使ってください： > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/Data-Science-For-Beginners.git > cd Data-Science-For-Beginners > git sparse-checkout set --no-cone '/*' '!translations' '!translated_images' > ``` -> これにより、コースを完了するために必要なすべてをより高速にダウンロードできます。 +> これにより、このコースの完了に必要なすべてが、より高速にダウンロードできます。 -**追加の翻訳言語のサポートを希望される場合は、[こちら](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)をご覧ください** +**追加の翻訳言語をご希望の場合は、[こちら](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)をご覧ください。** -#### コミュニティに参加しましょう +#### コミュニティに参加しよう [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Discordで進行中の「AIと学ぶシリーズ」について詳しくは、[Learn with AI Series](https://aka.ms/learnwithai/discord) をご覧ください。2025年9月18日から30日まで開催。GitHub Copilotのデータサイエンスでの活用に関するコツも得られます。 +Discordでの「AIと学ぶシリーズ」が開催中です。詳細および参加はこちらから：[Learn with AI Series](https://aka.ms/learnwithai/discord) 2025年9月18日〜30日。GitHub Copilotをデータサイエンスで活用するコツやヒントが得られます。 -![Learn with AI series](../../../../translated_images/ja/1.2b28cdc6205e26fe.webp) +![Learn with AI series](../../translated_images/ja/1.2b28cdc6205e26fe.webp) -# あなたは学生ですか？ +# 学生のあなたへ -以下のリソースから始めましょう： +以下のリソースから始めましょう: -- [学生ハブページ](https://docs.microsoft.com/en-gb/learn/student-hub?WT.mc_id=academic-77958-bethanycheum) このページには初心者向けリソース、学生パック、さらには無料認定バウチャーを取得する方法が記載されています。コンテンツは月に一度以上更新されるため、時々ブックマークしてチェックすることをお勧めします。 -- [Microsoft Learn Student Ambassadors](https://studentambassadors.microsoft.com?WT.mc_id=academic-77958-bethanycheum) グローバルな学生アンバサダーのコミュニティに参加しましょう。マイクロソフトへの道が開かれます。 +- [Student Hub ページ](https://docs.microsoft.com/en-gb/learn/student-hub?WT.mc_id=academic-77958-bethanycheum) このページでは、初心者向けリソース、学生パック、無料認定バウチャーの取得方法などが見つかります。最低でも月1回はブックマークして内容をチェックするとよいでしょう。 +- [Microsoft Learn Student Ambassadors](https://studentambassadors.microsoft.com?WT.mc_id=academic-77958-bethanycheum) グローバルな学生大使コミュニティに参加できます。Microsoftへの道を開くかもしれません。 # はじめに ## 📚 ドキュメント -- **[インストールガイド](INSTALLATION.md)** - 初心者向けのステップバイステップセットアップ手順 -- **[使い方ガイド](USAGE.md)** - 例と一般的なワークフロー -- **[トラブルシューティング](TROUBLESHOOTING.md)** - よくある問題の解決策 -- **[コントリビュートガイド](CONTRIBUTING.md)** - プロジェクトへの貢献方法 -- **[先生向け](for-teachers.md)** - 授業指導と教室リソース +- **[インストールガイド](INSTALLATION.md)** — 初心者向けのステップバイステップのセットアップ手順 +- **[使い方ガイド](USAGE.md)** — 例とよくあるワークフロー +- **[トラブルシューティング](TROUBLESHOOTING.md)** — よくある問題の解決策 +- **[貢献ガイド](CONTRIBUTING.md)** — このプロジェクトへの貢献方法 +- **[教師用](for-teachers.md)** — 教育指導と授業用リソース ## 👨‍🎓 学生向け -> **完全初心者向け**：データサイエンスが初めての方は、[初心者向けの例](examples/README.md)から始めましょう！シンプルでコメント付きの例が基本を理解するのに役立ちます。 -> **[学生向け](https://aka.ms/student-page)**: このカリキュラムを独自に利用する場合は、リポジトリ全体をフォークし、事前講義クイズから始めて課題を進めてください。講義を読んだら残りの活動を完了しましょう。解答コードをコピーするのではなく、内容を理解してプロジェクトを作成するよう心がけてください。解答コードは各プロジェクト指向レッスンの/solutionsフォルダーにあります。また、友人と勉強グループを作って一緒に学習するのも良いでしょう。さらに学習したい場合は [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/qprpajyoy3x0g7?WT.mc_id=academic-77958-bethanycheum) をお勧めします。 +> **完全初心者の方へ**：データサイエンスが初めてですか？まずは[初心者向けの例](examples/README.md)から始めてください！これらのシンプルでコメント付きの例は、カリキュラムの全体に取り掛かる前に基礎を理解するのに役立ちます。 +> **[学生](https://aka.ms/student-page)**：このカリキュラムを自分で使うには、リポジトリ全体をフォークして、レッスン前のクイズから始めて演習を進めてください。その後、講義を読み、残りの活動を完了します。解答コードを単にコピーするのではなく、レッスン内容を理解してプロジェクトを作成することを推奨します。解答コードは各プロジェクト指向レッスンの /solutions フォルダーに用意されています。友人と学習グループを作り、一緒に内容を学ぶのも良い方法です。さらなる学習には、[Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/qprpajyoy3x0g7?WT.mc_id=academic-77958-bethanycheum) をお勧めします。 -**クイックスタート：** -1. [インストールガイド](INSTALLATION.md) を確認し環境をセットアップしてください -2. [使い方ガイド](USAGE.md) に目を通し、カリキュラムの利用方法を学びましょう -3. レッスン1から順に進めてください -4. サポートが必要なら[Discordコミュニティ](https://aka.ms/ds4beginners/discord)に参加しましょう +**クイックスタート:** +1. 環境構築は [インストールガイド](INSTALLATION.md) を確認 +2. カリキュラムの使い方は [使い方ガイド](USAGE.md) を参照 +3. レッスン1から順に進める +4. サポートが必要なら [Discordコミュニティ](https://aka.ms/ds4beginners/discord) に参加 ## 👩‍🏫 教師向け -> **先生方へ**：このカリキュラムの活用方法について[いくつかの提案](for-teachers.md)を含めています。ご意見は[ディスカッションフォーラム](https://github.com/microsoft/Data-Science-For-Beginners/discussions)でお待ちしています！ - +> **教師の皆様へ**：[このカリキュラムの活用方法についての提案](for-teachers.md)を含めています。ぜひ [ディスカッションフォーラム](https://github.com/microsoft/Data-Science-For-Beginners/discussions) にてご意見をお寄せください！ ## チーム紹介 -[![Promo video](../../ds-for-beginners.gif)](https://youtu.be/8mzavjQSMM4 "Promo video") -**Gif by** [Mohit Jaisal](https://www.linkedin.com/in/mohitjaisal) +[![プロモーションビデオ](../../ds-for-beginners.gif)](https://youtu.be/8mzavjQSMM4 "プロモーションビデオ") + +**Gif作成者** [Mohit Jaisal](https://www.linkedin.com/in/mohitjaisal) -> 🎥 上の画像をクリックすると、このプロジェクトとそれを作成した人たちについてのビデオがご覧いただけます！ +> 🎥 上の画像をクリックすると、このプロジェクトとそれを作成した人々についてのビデオをご覧いただけます！ ## 教育方針 -このカリキュラムを作成する際、私たちは2つの教育の原則を選びました：プロジェクトベースであることと、頻繁なクイズを含むこと。シリーズの最後には、学生はデータサイエンスの基本原則を学びます。これには倫理的な概念、データ準備、データのさまざまな扱い方、データ可視化、データ分析、データサイエンスの実世界の活用例などが含まれます。 +このカリキュラムを構築する際に、私たちは２つの教育の原則を選びました：プロジェクトベースであることと、頻繁にクイズを含めることです。このシリーズを終える頃には、学生はデータサイエンスの基本原則、倫理的概念、データ準備、さまざまなデータの扱い方、データビジュアライゼーション、データ分析、データサイエンスの実例などを学んでいることでしょう。 -さらに、授業前の低リスクのクイズは学生の学習意欲を高め、授業後の2回目のクイズは理解の定着を助けます。このカリキュラムは柔軟で楽しく学べるよう設計されており、全体または一部だけ取り組むことも可能です。プロジェクトは小さなものから始まり、10週間のサイクルの終わりにはより複雑になります。 +また、授業の前に行う低負荷のクイズは、学生が特定のトピックの学習に集中する意図を設定し、授業後のクイズがさらに記憶の定着を助けます。このカリキュラムは柔軟で楽しく設計されており、全体または一部だけでも受講できます。プロジェクトは小さく始まり、10週間のサイクルの終わりまでに徐々に複雑になります。 -> [行動規範](CODE_OF_CONDUCT.md)、[貢献ガイド](CONTRIBUTING.md)、[翻訳ガイド](TRANSLATIONS.md)をご覧ください。建設的なフィードバックを歓迎します！ +> 私たちの[行動規範](CODE_OF_CONDUCT.md)、[貢献ガイドライン](CONTRIBUTING.md)、[翻訳ガイドライン](TRANSLATIONS.md)もご覧ください。建設的なフィードバックをお待ちしています！ -## 各レッスンに含まれるもの： +## 各レッスンには以下が含まれます： - 任意のスケッチノート -- 任意の補足動画 -- 授業前ウォームアップクイズ -- 書かれたレッスン内容 -- プロジェクトベースのレッスンには、プロジェクトを作成するためのステップバイステップガイド -- 知識チェック +- 任意の補足ビデオ +- 授業前のウォームアップクイズ +- 文章によるレッスン +- プロジェクトベースのレッスンの場合、プロジェクトの段階的な作成ガイド +- 知識確認 - チャレンジ -- 補足読書 +- 補助読書 - 課題 -- [授業後クイズ](https://ff-quizzes.netlify.app/en/) +- [授業後のクイズ](https://ff-quizzes.netlify.app/en/) -> **クイズについての注意**：すべてのクイズはQuiz-Appフォルダーにあり、合計40回分の3問ずつのクイズです。レッスン内からリンクされていますが、クイズアプリはローカルでも起動でき、Azureに展開も可能です。`quiz-app`フォルダーの指示に従ってください。現在、順次ローカライズ中です。 +> **クイズについての注意**: 全てのクイズはQuiz-Appフォルダーに収められており、計40回のクイズで各回３問ずつあります。クイズはレッスン内からリンクされていますが、クイズアプリはローカルで実行したりAzureにデプロイすることも可能です。`quiz-app`フォルダーの指示に従ってください。現在、順次ローカライズが進められています。 -## 🎓 初心者向けの例 +## 🎓 初心者に優しい例 -**データサイエンスが初めてですか？** スタートアップに役立つシンプルでコメント付きのコードを集めた特別な[examplesディレクトリ](examples/README.md)を作成しました： +**データサイエンスが初めてですか？** 簡単で丁寧にコメントされたコードを揃えた特別な[examplesディレクトリ](examples/README.md)をご用意しています： -- 🌟 **Hello World** - 最初のデータサイエンスプログラム -- 📂 **データの読み込み** - データセットの読み込みと探索を学ぶ -- 📊 **シンプルな分析** - 統計計算とパターンの発見 -- 📈 **基本的な可視化** - チャートとグラフの作成 -- 🔬 **実世界プロジェクト** - 最初から最後までのワークフロー +- 🌟 **Hello World** - あなたの最初のデータサイエンスプログラム +- 📂 **データの読み込み** - データセットを読み込み、探索する方法を学びます +- 📊 **簡単な分析** - 統計を計算しパターンを見つけます +- 📈 **基本的なビジュアライゼーション** - チャートやグラフを作成します +- 🔬 **実世界プロジェクト** - 初めから完成までのワークフローを体験します -各例には詳細なコメントがあり、全ステップを説明しているため、完全な初心者にも最適です！ +各例には細かいコメントが全手順について説明されており、完全な初心者に最適です！ 👉 **[例から始める](examples/README.md)** 👈 ## レッスン -|![ @sketchthedocsによるスケッチノート https://sketchthedocs.dev](../../../../translated_images/ja/00-Roadmap.4905d6567dff4753.webp)| +|![ @sketchthedocsによるスケッチノート https://sketchthedocs.dev](../../translated_images/ja/00-Roadmap.4905d6567dff4753.webp)| |:---:| -| Data Science For Beginners: ロードマップ - _スケッチノート [@nitya](https://twitter.com/nitya)_ | +| データサイエンス入門: ロードマップ - _[@nitya](https://twitter.com/nitya)によるスケッチノート_ | -| レッスン番号 | トピック | レッスングループ | 学習目標 | 関連レッスン | 著者 | +| レッスン番号 | トピック | レッスングループ | 学習目標 | リンクされたレッスン | 著者 | | :-----------: | :----------------------------------------: | :--------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------: | :----: | -| 01 | データサイエンスの定義 | [イントロダクション](1-Introduction/README.md) | データサイエンスの基本概念、人工知能、機械学習、ビッグデータとの関連性を学びます。 | [lesson](1-Introduction/01-defining-data-science/README.md) [video](https://youtu.be/beZ7Mb_oz9I) | [Dmitry](http://soshnikov.com) | -| 02 | データサイエンス倫理 | [イントロダクション](1-Introduction/README.md) | データ倫理の概念、課題とフレームワーク。 | [lesson](1-Introduction/02-ethics/README.md) | [Nitya](https://twitter.com/nitya) | -| 03 | データの定義 | [イントロダクション](1-Introduction/README.md) | データの分類と一般的なデータソース。 | [lesson](1-Introduction/03-defining-data/README.md) | [Jasmine](https://www.twitter.com/paladique) | -| 04 | 統計学と確率の入門 | [イントロダクション](1-Introduction/README.md) | データを理解するための確率と統計の数学的手法。 | [lesson](1-Introduction/04-stats-and-probability/README.md) [video](https://youtu.be/Z5Zy85g4Yjw) | [Dmitry](http://soshnikov.com) | -| 05 | リレーショナルデータの扱い | [データ操作](2-Working-With-Data/README.md) | リレーショナルデータの紹介と、SQL（シーケル）を使った探索と分析の基本。 | [lesson](2-Working-With-Data/05-relational-databases/README.md) | [Christopher](https://www.twitter.com/geektrainer) | | | -| 06 | NoSQLデータの取り扱い | [データ操作](2-Working-With-Data/README.md) | 非リレーショナルデータの紹介、その種類とドキュメントデータベースの基本的な探索と分析。 | [lesson](2-Working-With-Data/06-non-relational/README.md) | [Jasmine](https://twitter.com/paladique)| -| 07 | Pythonでの操作 | [データ操作](2-Working-With-Data/README.md) | Pandasなどのライブラリを使ったPythonによるデータ探索の基礎。Pythonの基礎知識が推奨されます。 | [lesson](2-Working-With-Data/07-python/README.md) [video](https://youtu.be/dZjWOGbsN4Y) | [Dmitry](http://soshnikov.com) | -| 08 | データ準備 | [データ操作](2-Working-With-Data/README.md) | 欠損、不正確、不完全なデータの課題に対応するためのデータのクリーニングと変換技術。 | [lesson](2-Working-With-Data/08-data-preparation/README.md) | [Jasmine](https://www.twitter.com/paladique) | -| 09 | 量の可視化 | [データ可視化](3-Data-Visualization/README.md) | Matplotlibを使って鳥データを可視化する方法 🦆 | [lesson](3-Data-Visualization/09-visualization-quantities/README.md) | [Jen](https://twitter.com/jenlooper) | -| 10 | データ分布の可視化 | [データ可視化](3-Data-Visualization/README.md) | 観測値と傾向を区間内で可視化。 | [lesson](3-Data-Visualization/10-visualization-distributions/README.md) | [Jen](https://twitter.com/jenlooper) | -| 11 | 割合の可視化 | [データ可視化](3-Data-Visualization/README.md) | 離散的かつグループ化されたパーセンテージの可視化。 | [lesson](3-Data-Visualization/11-visualization-proportions/README.md) | [Jen](https://twitter.com/jenlooper) | -| 12 | 関係性の可視化 | [データ可視化](3-Data-Visualization/README.md) | データや変数の集合間のつながりや相関を可視化。 | [lesson](3-Data-Visualization/12-visualization-relationships/README.md) | [Jen](https://twitter.com/jenlooper) | -| 13 | 意義のある可視化 | [データ可視化](3-Data-Visualization/README.md) | 有効な問題解決や洞察を得るための可視化の技術と指針。 | [lesson](3-Data-Visualization/13-meaningful-visualizations/README.md) | [Jen](https://twitter.com/jenlooper) | -| 14 | データサイエンスライフサイクル入門 | [ライフサイクル](4-Data-Science-Lifecycle/README.md) | データサイエンスライフサイクルと最初のステップであるデータの取得と抽出についての紹介。 | [lesson](4-Data-Science-Lifecycle/14-Introduction/README.md) | [Jasmine](https://twitter.com/paladique) | -| 15 | 分析 | [ライフサイクル](4-Data-Science-Lifecycle/README.md) | データサイエンスライフサイクルのこの段階では、データ分析手法に焦点を当てる。 | [lesson](4-Data-Science-Lifecycle/15-analyzing/README.md) | [Jasmine](https://twitter.com/paladique) | | | -| 16 | コミュニケーション | [ライフサイクル](4-Data-Science-Lifecycle/README.md) | データからの洞察を意思決定者が理解しやすい形で伝えることに集中する段階。 | [lesson](4-Data-Science-Lifecycle/16-communication/README.md) | [Jalen](https://twitter.com/JalenMcG) | | | -| 17 | クラウドにおけるデータサイエンス | [クラウドデータ](5-Data-Science-In-Cloud/README.md) | クラウドのデータサイエンスとその利点を紹介する一連のレッスン。 | [lesson](5-Data-Science-In-Cloud/17-Introduction/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) | -| 18 | クラウドにおけるデータサイエンス | [クラウドデータ](5-Data-Science-In-Cloud/README.md) | ローコードツールを使ったモデルのトレーニング。 |[lesson](5-Data-Science-In-Cloud/18-Low-Code/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) | -| 19 | クラウドにおけるデータサイエンス | [クラウドデータ](5-Data-Science-In-Cloud/README.md) | Azure Machine Learning Studioを使ったモデルのデプロイ。 | [lesson](5-Data-Science-In-Cloud/19-Azure/README.md)| [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) | -| 20 | 実世界のデータサイエンス | [実世界](6-Data-Science-In-Wild/README.md) | 実世界でのデータサイエンスに基づくプロジェクト。 | [lesson](6-Data-Science-In-Wild/20-Real-World-Examples/README.md) | [Nitya](https://twitter.com/nitya) | +| 01 | データサイエンスの定義 | [Introduction](1-Introduction/README.md) | データサイエンスの基礎概念と、それが人工知能、機械学習、ビッグデータとどう関連するかを学ぶ。 | [lesson](1-Introduction/01-defining-data-science/README.md) [video](https://youtu.be/beZ7Mb_oz9I) | [Dmitry](http://soshnikov.com) | +| 02 | データサイエンス倫理 | [Introduction](1-Introduction/README.md) | データ倫理の概念、課題、フレームワーク。 | [lesson](1-Introduction/02-ethics/README.md) | [Nitya](https://twitter.com/nitya) | +| 03 | データの定義 | [Introduction](1-Introduction/README.md) | データの分類方法とその一般的なソース。 | [lesson](1-Introduction/03-defining-data/README.md) | [Jasmine](https://www.twitter.com/paladique) | +| 04 | 統計学と確率の入門 | [Introduction](1-Introduction/README.md) | データを理解するための確率と統計の数学的手法。 | [lesson](1-Introduction/04-stats-and-probability/README.md) [video](https://youtu.be/Z5Zy85g4Yjw) | [Dmitry](http://soshnikov.com) | +| 05 | リレーショナルデータの扱い方 | [Working With Data](2-Working-With-Data/README.md) | リレーショナルデータの入門と、構造化問い合わせ言語（SQL）を使った基本的な探索・分析の方法。 | [lesson](2-Working-With-Data/05-relational-databases/README.md) | [Christopher](https://www.twitter.com/geektrainer) | | | +| 06 | NoSQLデータの扱い方 | [Working With Data](2-Working-With-Data/README.md) | 非リレーショナルデータの入門、その多様なタイプ、ドキュメントデータベースの基本的な探索と解析方法。 | [lesson](2-Working-With-Data/06-non-relational/README.md) | [Jasmine](https://twitter.com/paladique)| +| 07 | Pythonでのデータ操作 | [Working With Data](2-Working-With-Data/README.md) | Pandasなどのライブラリを使ったPythonによるデータ探索の基礎。Pythonプログラミングの基礎理解が推奨されます。 | [lesson](2-Working-With-Data/07-python/README.md) [video](https://youtu.be/dZjWOGbsN4Y) | [Dmitry](http://soshnikov.com) | +| 08 | データ準備 | [Working With Data](2-Working-With-Data/README.md) | 欠損、不正確、不完全なデータの課題に対処するためのクリーニングや変換の技術。 | [lesson](2-Working-With-Data/08-data-preparation/README.md) | [Jasmine](https://www.twitter.com/paladique) | +| 09 | 量の可視化 | [Data Visualization](3-Data-Visualization/README.md) | Matplotlibを使った鳥データの可視化を学びます 🦆 | [lesson](3-Data-Visualization/09-visualization-quantities/README.md) | [Jen](https://twitter.com/jenlooper) | +| 10 | データ分布の可視化 | [Data Visualization](3-Data-Visualization/README.md) | 観測値や傾向を一定範囲内で視覚化。 | [lesson](3-Data-Visualization/10-visualization-distributions/README.md) | [Jen](https://twitter.com/jenlooper) | +| 11 | 割合の可視化 | [Data Visualization](3-Data-Visualization/README.md) | 離散的およびグループ化されたパーセンテージの可視化。 | [lesson](3-Data-Visualization/11-visualization-proportions/README.md) | [Jen](https://twitter.com/jenlooper) | +| 12 | 関係性の可視化 | [Data Visualization](3-Data-Visualization/README.md) | データセットとその変数間の関係性と相関の可視化。 | [lesson](3-Data-Visualization/12-visualization-relationships/README.md) | [Jen](https://twitter.com/jenlooper) | +| 13 | 意味のあるビジュアライゼーション | [Data Visualization](3-Data-Visualization/README.md) | 効果的な問題解決と洞察のために価値あるビジュアライゼーションを作成するテクニックと指針。 | [lesson](3-Data-Visualization/13-meaningful-visualizations/README.md) | [Jen](https://twitter.com/jenlooper) | +| 14 | データサイエンスのライフサイクル入門 | [Lifecycle](4-Data-Science-Lifecycle/README.md) | データサイエンスのライフサイクルと、最初のステップであるデータ獲得と抽出の紹介。 | [lesson](4-Data-Science-Lifecycle/14-Introduction/README.md) | [Jasmine](https://twitter.com/paladique) | +| 15 | 分析 | [Lifecycle](4-Data-Science-Lifecycle/README.md) | データサイエンスのライフサイクルのこのフェーズは、データを分析する技術に焦点を当てます。 | [lesson](4-Data-Science-Lifecycle/15-analyzing/README.md) | [Jasmine](https://twitter.com/paladique) | | | +| 16 | コミュニケーション | [Lifecycle](4-Data-Science-Lifecycle/README.md) | データサイエンスのライフサイクルのこのフェーズは、意思決定者が理解しやすい形でデータから得られた洞察を伝えることに重点を置きます。 | [lesson](4-Data-Science-Lifecycle/16-communication/README.md) | [Jalen](https://twitter.com/JalenMcG) | | | +| 17 | クラウドにおけるデータサイエンス | [Cloud Data](5-Data-Science-In-Cloud/README.md) | クラウドにおけるデータサイエンスとその利点の紹介。 | [lesson](5-Data-Science-In-Cloud/17-Introduction/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) と [Maud](https://twitter.com/maudstweets) | +| 18 | クラウドにおけるデータサイエンス | [Cloud Data](5-Data-Science-In-Cloud/README.md) | ローコードツールを使用したモデルのトレーニング。 |[lesson](5-Data-Science-In-Cloud/18-Low-Code/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) と [Maud](https://twitter.com/maudstweets) | +| 19 | クラウドにおけるデータサイエンス | [Cloud Data](5-Data-Science-In-Cloud/README.md) | Azure Machine Learning Studioを用いたモデルのデプロイ。 | [lesson](5-Data-Science-In-Cloud/19-Azure/README.md)| [Tiffany](https://twitter.com/TiffanySouterre) と [Maud](https://twitter.com/maudstweets) | +| 20 | 現実世界のデータサイエンス | [In the Wild](6-Data-Science-In-Wild/README.md) | 現実世界で行われるデータサイエンス駆動のプロジェクト。 | [lesson](6-Data-Science-In-Wild/20-Real-World-Examples/README.md) | [Nitya](https://twitter.com/nitya) | ## GitHub Codespaces -このサンプルをCodespaceで開くには以下の手順を実行してください： -1. Codeのドロップダウンメニューをクリックし、「Open with Codespaces」オプションを選択します。 -2. ペインの下部で「+ New codespace」を選択します。 +このサンプルをCodespaceで開くには、以下の手順を実行してください： +1. Codeドロップダウンメニューをクリックし、「Open with Codespaces」オプションを選択します。 +2. ペイン下部の「+ New codespace」を選択します。 詳細は[GitHubのドキュメント](https://docs.github.com/en/codespaces/developing-in-codespaces/creating-a-codespace-for-a-repository#creating-a-codespace)をご覧ください。 ## VSCode Remote - Containers -このリポジトリをローカルマシンとVSCodeを使い、VS Code Remote - Containers拡張機能を利用してコンテナ内で開く手順： -1. 開発用コンテナを初めて使う場合、[動作環境準備のドキュメント](https://code.visualstudio.com/docs/devcontainers/containers#_getting-started)にある必要条件（例：Dockerのインストールなど）を満たしているか確認してください。 +ローカルマシンとVSCodeのRemote - Containers拡張機能を使って、このリポジトリをコンテナ内で開くには以下の手順： + +1. 開発コンテナを初めて使う場合は、システムが[はじめにドキュメント](https://code.visualstudio.com/docs/devcontainers/containers#_getting-started)に記載の前提条件（例：Dockerのインストール）を満たしていることを確認してください。 + +このリポジトリを使用するには、以下のいずれかを行います： -このリポジトリを使うには、リポジトリを隔離されたDockerボリューム内で開く方法があります： +ローカルのファイルシステムではなくDockerボリューム内でリポジトリを開く： -**メモ**：内部的には、ソースコードをローカルファイルシステムではなくDockerボリュームにクローンする「Remote-Containers: Clone Repository in Container Volume...」コマンドを使用します。[ボリューム](https://docs.docker.com/storage/volumes/)はコンテナデータの永続化に適しています。 +**注意**：内部的には、Remote-Containersの「Clone Repository in Container Volume...」コマンドを使ってリポジトリのソースコードをDockerボリュームにクローンします。[ボリューム](https://docs.docker.com/storage/volumes/)はコンテナデータの永続化に推奨される方法です。 -またはローカルにクローンまたはダウンロードしたリポジトリを開く方法： +またはローカルにクローンまたはダウンロードしたリポジトリを開く： -- このリポジトリをローカルファイルシステムにクローンします。 -- F1キーを押して「Remote-Containers: Open Folder in Container...」コマンドを選択します。 -- クローンしたフォルダーを選び、コンテナの起動を待ち、試してみてください。 +- このリポジトリをローカルのファイルシステムにクローンします。 +- F1を押して「Remote-Containers: Open Folder in Container...」コマンドを選択します。 +- クローンしたフォルダーを選択し、コンテナの起動を待ってから試してみてください。 ## オフラインアクセス -[Docsify](https://docsify.js.org/#/)を使って、このドキュメントをオフラインで閲覧できます。リポジトリをフォークし、[Docsifyをローカルにインストール](https://docsify.js.org/#/quickstart)してから、このリポジトリのルートフォルダーで `docsify serve` と入力してください。ウェブサイトはlocalhostの3000ポートで提供されます：`localhost:3000`。 +[Docsify](https://docsify.js.org/#/)を使用してこのドキュメントをオフラインで閲覧可能です。このリポジトリをフォークし、ローカルマシンに[Docsifyをインストール](https://docsify.js.org/#/quickstart)してから、このリポジトリのルートフォルダで `docsify serve` を実行してください。ウェブサイトはローカルホストの3000番ポート（`localhost:3000`）でサーブされます。 -> 注意：ノートブックはDocsifyでレンダリングされないため、ノートブックを実行する場合はVS CodeのPythonカーネルで別途行ってください。 +> 注意：ノートブックはDocsifyではレンダリングされないため、ノートブックを実行する必要がある場合はPythonカーネルを動かすVS Code内で別途実行してください。 ## その他のカリキュラム -私たちのチームは他のカリキュラムも提供しています！ぜひご覧ください： +私たちのチームは他のカリキュラムも提供しています！ご覧ください： ### LangChain @@ -216,7 +210,7 @@ Discordで進行中の「AIと学ぶシリーズ」について詳しくは、[L --- -### 生成AIシリーズ +### 生成系AIシリーズ [![Generative AI for Beginners](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) [![Generative AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) [![Generative AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) @@ -224,7 +218,7 @@ Discordで進行中の「AIと学ぶシリーズ」について詳しくは、[L --- -### コア学習 +### コアラーニング [![ML for Beginners](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) [![Data Science for Beginners](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) [![AI for Beginners](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) @@ -243,13 +237,13 @@ Discordで進行中の「AIと学ぶシリーズ」について詳しくは、[L ## ヘルプを得る -**問題に直面していますか？** よくある問題の解決策については、[トラブルシューティングガイド](TROUBLESHOOTING.md)を確認してください。 +**問題が発生しましたか？** 一般的な問題の解決策については、[トラブルシューティングガイド](TROUBLESHOOTING.md)を参照してください。 -AIアプリの構築で詰まったり質問がある場合は、学習者や経験豊富な開発者と一緒にMCPについて話し合うコミュニティに参加してください。ここは質問が歓迎され、知識が自由に共有される支援的なコミュニティです。 +AIアプリの構築で立ち止まったり質問がある場合は、MCPに関する議論に参加してください。質問が歓迎され、知識が自由に共有されるサポートコミュニティです。 [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -製品フィードバックや開発中のエラーについては、以下を訪問してください： +製品のフィードバックや構築中のエラーがある場合は、こちらをご利用ください： [![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) @@ -257,5 +251,5 @@ AIアプリの構築で詰まったり質問がある場合は、学習者や経 **免責事項**： -本書類はAI翻訳サービス［Co-op Translator］(https://github.com/Azure/co-op-translator)を使用して翻訳されています。正確性には努めておりますが、自動翻訳には誤りや不正確な部分が含まれる可能性があります。原文の言語によるオリジナル資料が正本として取り扱われるべきです。重要な情報については、専門の翻訳者による翻訳をお勧めします。本翻訳の使用に起因するいかなる誤解や解釈の相違についても、当方は一切の責任を負いかねます。 +本書類はAI翻訳サービス「[Co-op Translator](https://github.com/Azure/co-op-translator)」を使用して翻訳されています。正確さには努めておりますが、自動翻訳には誤りや不正確な部分が含まれる場合があります。原文（原言語版）が正式な情報源とみなされるべきです。重要な情報については、専門の人間による翻訳を推奨します。本翻訳の使用により生じた誤解や解釈の相違について、当社は一切の責任を負いかねます。 \ No newline at end of file diff --git a/translations/ja/SECURITY.md b/translations/ja/SECURITY.md index c681fe73..9a4d5b7d 100644 --- a/translations/ja/SECURITY.md +++ b/translations/ja/SECURITY.md @@ -1,12 +1,3 @@ - ## セキュリティ Microsoftは、ソフトウェア製品やサービスのセキュリティを非常に重視しています。これには、[Microsoft](https://github.com/Microsoft)、[Azure](https://github.com/Azure)、[DotNet](https://github.com/dotnet)、[AspNet](https://github.com/aspnet)、[Xamarin](https://github.com/xamarin)、および[弊社のGitHub組織](https://opensource.microsoft.com/)で管理されているすべてのソースコードリポジトリが含まれます。 diff --git a/translations/ja/SUPPORT.md b/translations/ja/SUPPORT.md index 17726bb9..f950a840 100644 --- a/translations/ja/SUPPORT.md +++ b/translations/ja/SUPPORT.md @@ -1,12 +1,3 @@ - # サポート ## 問題の報告方法とヘルプの取得 diff --git a/translations/ja/TROUBLESHOOTING.md b/translations/ja/TROUBLESHOOTING.md index 3ea558fa..b29f4ec9 100644 --- a/translations/ja/TROUBLESHOOTING.md +++ b/translations/ja/TROUBLESHOOTING.md @@ -1,12 +1,3 @@ - # トラブルシューティングガイド このガイドでは、Data Science for Beginners カリキュラムを使用する際に遭遇する可能性のある一般的な問題の解決策を提供します。 diff --git a/translations/ja/USAGE.md b/translations/ja/USAGE.md index afe959ca..e6f005a1 100644 --- a/translations/ja/USAGE.md +++ b/translations/ja/USAGE.md @@ -1,12 +1,3 @@ - # 使用ガイド このガイドでは、「初心者のためのデータサイエンス」カリキュラムの使用例と一般的なワークフローを紹介します。 diff --git a/translations/ja/docs/_sidebar.md b/translations/ja/docs/_sidebar.md index 99e7136e..465063a4 100644 --- a/translations/ja/docs/_sidebar.md +++ b/translations/ja/docs/_sidebar.md @@ -1,12 +1,3 @@ - - はじめに - [データサイエンスの定義](../1-Introduction/01-defining-data-science/README.md) - [データサイエンスの倫理](../1-Introduction/02-ethics/README.md) diff --git a/translations/ja/examples/README.md b/translations/ja/examples/README.md index 2868e476..4fbf6dc1 100644 --- a/translations/ja/examples/README.md +++ b/translations/ja/examples/README.md @@ -1,12 +1,3 @@ - # 初心者向けデータサイエンスの例 例のディレクトリへようこそ！このコレクションは、シンプルでコメントが充実した例を集めたもので、データサイエンスを始めたい初心者の方に最適です。 diff --git a/translations/ja/for-teachers.md b/translations/ja/for-teachers.md index 011f24cf..653e6549 100644 --- a/translations/ja/for-teachers.md +++ b/translations/ja/for-teachers.md @@ -1,12 +1,3 @@ - ## 教育者の皆様へ このカリキュラムを教室で使用してみませんか？ぜひご活用ください！ diff --git a/translations/ja/quiz-app/README.md b/translations/ja/quiz-app/README.md index ee4d1f4a..39f4a2ef 100644 --- a/translations/ja/quiz-app/README.md +++ b/translations/ja/quiz-app/README.md @@ -1,12 +1,3 @@ - # クイズ これらのクイズは、データサイエンスカリキュラム（https://aka.ms/datascience-beginners）の講義前後に行うクイズです。 diff --git a/translations/ja/sketchnotes/README.md b/translations/ja/sketchnotes/README.md index 2fc59772..0dc3c15b 100644 --- a/translations/ja/sketchnotes/README.md +++ b/translations/ja/sketchnotes/README.md @@ -1,12 +1,3 @@ - すべてのスケッチノートはこちらで見つけることができます！ ## クレジット diff --git a/translations/ko/.co-op-translator.json b/translations/ko/.co-op-translator.json new file mode 100644 index 00000000..d2e8562b --- /dev/null +++ b/translations/ko/.co-op-translator.json @@ -0,0 +1,422 @@ +{ + "1-Introduction/01-defining-data-science/README.md": { + "original_hash": "43212cc1ac137b7bb1dcfb37ca06b0f4", + "translation_date": "2025-10-25T18:42:41+00:00", + "source_file": 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"translation_date": "2025-10-03T12:58:54+00:00", + "source_file": "examples/README.md", + "language_code": "ko" + }, + "for-teachers.md": { + "original_hash": "f7440be10c17a8a9262713af3d2818a9", + "translation_date": "2025-09-06T19:54:05+00:00", + "source_file": "for-teachers.md", + "language_code": "ko" + }, + "quiz-app/README.md": { + "original_hash": "e92c33ea498915a13c9aec162616db18", + "translation_date": "2025-08-25T17:40:28+00:00", + "source_file": "quiz-app/README.md", + "language_code": "ko" + }, + "sketchnotes/README.md": { + "original_hash": "3a848466cb63aff1a93411affb152c2a", + "translation_date": "2025-08-25T17:11:49+00:00", + "source_file": "sketchnotes/README.md", + "language_code": "ko" + } +} \ No newline at end of file diff --git a/translations/ko/1-Introduction/01-defining-data-science/README.md b/translations/ko/1-Introduction/01-defining-data-science/README.md index 7dcb7508..73f451ae 100644 --- a/translations/ko/1-Introduction/01-defining-data-science/README.md +++ b/translations/ko/1-Introduction/01-defining-data-science/README.md @@ -1,12 +1,3 @@ - # 데이터 과학 정의 | ![ [(@sketchthedocs)](https://sketchthedocs.dev) 의 스케치노트 ](../../sketchnotes/01-Definitions.png) | diff --git a/translations/ko/1-Introduction/01-defining-data-science/assignment.md b/translations/ko/1-Introduction/01-defining-data-science/assignment.md index f070caff..55bc79d8 100644 --- a/translations/ko/1-Introduction/01-defining-data-science/assignment.md +++ b/translations/ko/1-Introduction/01-defining-data-science/assignment.md @@ -1,12 +1,3 @@ - # 과제: 데이터 과학 시나리오 이 첫 번째 과제에서는 다양한 문제 영역에서 실제 생활의 프로세스나 문제를 생각해보고, 데이터 과학 프로세스를 사용하여 이를 어떻게 개선할 수 있는지 고민해 보세요. 다음을 고려해 보세요: diff --git a/translations/ko/1-Introduction/01-defining-data-science/solution/assignment.md b/translations/ko/1-Introduction/01-defining-data-science/solution/assignment.md index d9645564..b7878109 100644 --- a/translations/ko/1-Introduction/01-defining-data-science/solution/assignment.md +++ b/translations/ko/1-Introduction/01-defining-data-science/solution/assignment.md @@ -1,12 +1,3 @@ - # 과제: 데이터 과학 시나리오 이 첫 번째 과제에서는 다양한 문제 영역에서 실제 프로세스나 문제를 생각하고, 데이터 과학 프로세스를 사용하여 이를 개선할 방법을 고민해 보세요. 다음을 고려해 보세요: diff --git a/translations/ko/1-Introduction/02-ethics/README.md b/translations/ko/1-Introduction/02-ethics/README.md index 927eb408..5766a8ff 100644 --- a/translations/ko/1-Introduction/02-ethics/README.md +++ b/translations/ko/1-Introduction/02-ethics/README.md @@ -1,12 +1,3 @@ - # 데이터 윤리 소개 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/02-Ethics.png)| diff --git a/translations/ko/1-Introduction/02-ethics/assignment.md b/translations/ko/1-Introduction/02-ethics/assignment.md index 80c9d01b..0e6c4641 100644 --- a/translations/ko/1-Introduction/02-ethics/assignment.md +++ b/translations/ko/1-Introduction/02-ethics/assignment.md @@ -1,12 +1,3 @@ - ## 데이터 윤리 사례 연구 작성하기 ## 지침 diff --git a/translations/ko/1-Introduction/03-defining-data/README.md b/translations/ko/1-Introduction/03-defining-data/README.md index c6195877..0293a108 100644 --- a/translations/ko/1-Introduction/03-defining-data/README.md +++ b/translations/ko/1-Introduction/03-defining-data/README.md @@ -1,12 +1,3 @@ - # 데이터 정의하기 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/03-DefiningData.png)| diff --git a/translations/ko/1-Introduction/03-defining-data/assignment.md b/translations/ko/1-Introduction/03-defining-data/assignment.md index 315abb7d..940de197 100644 --- a/translations/ko/1-Introduction/03-defining-data/assignment.md +++ b/translations/ko/1-Introduction/03-defining-data/assignment.md @@ -1,12 +1,3 @@ - # 데이터셋 분류 ## 지침 diff --git a/translations/ko/1-Introduction/04-stats-and-probability/README.md b/translations/ko/1-Introduction/04-stats-and-probability/README.md index 119cd632..3989afd6 100644 --- a/translations/ko/1-Introduction/04-stats-and-probability/README.md +++ b/translations/ko/1-Introduction/04-stats-and-probability/README.md @@ -1,12 +1,3 @@ - # 통계와 확률에 대한 간단한 소개 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/04-Statistics-Probability.png)| @@ -64,7 +55,7 @@ CO_OP_TRANSLATOR_METADATA: 중앙값과 사분위수의 관계를 그래픽으로 나타낸 것이 **박스 플롯**입니다: -박스 플롯 설명 +박스 플롯 설명 여기서 **사분위 범위** IQR=Q3-Q1을 계산하며, **이상치**는 [Q1-1.5*IQR, Q3+1.5*IQR] 범위를 벗어난 값을 의미합니다. diff --git a/translations/ko/1-Introduction/04-stats-and-probability/assignment.md b/translations/ko/1-Introduction/04-stats-and-probability/assignment.md index b9ccd969..369fc331 100644 --- a/translations/ko/1-Introduction/04-stats-and-probability/assignment.md +++ b/translations/ko/1-Introduction/04-stats-and-probability/assignment.md @@ -1,12 +1,3 @@ - # 소규모 당뇨병 연구 이 과제에서는 [여기](https://www4.stat.ncsu.edu/~boos/var.select/diabetes.html)에서 가져온 소규모 당뇨병 환자 데이터셋을 다룰 것입니다. diff --git a/translations/ko/1-Introduction/README.md b/translations/ko/1-Introduction/README.md index c95a7477..ceda9538 100644 --- a/translations/ko/1-Introduction/README.md +++ b/translations/ko/1-Introduction/README.md @@ -1,12 +1,3 @@ - # 데이터 과학 입문 ![데이터 활용](../../../translated_images/ko/data.48e22bb7617d8d92188afbc4c48effb920ba79f5cebdc0652cd9f34bbbd90c18.jpg) diff --git a/translations/ko/2-Working-With-Data/05-relational-databases/README.md b/translations/ko/2-Working-With-Data/05-relational-databases/README.md index c7d2d961..c6398bc2 100644 --- a/translations/ko/2-Working-With-Data/05-relational-databases/README.md +++ b/translations/ko/2-Working-With-Data/05-relational-databases/README.md @@ -1,12 +1,3 @@ - # 데이터 작업: 관계형 데이터베이스 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/05-RelationalData.png)| diff --git a/translations/ko/2-Working-With-Data/05-relational-databases/assignment.md b/translations/ko/2-Working-With-Data/05-relational-databases/assignment.md index 704550c5..99f9ded3 100644 --- a/translations/ko/2-Working-With-Data/05-relational-databases/assignment.md +++ b/translations/ko/2-Working-With-Data/05-relational-databases/assignment.md @@ -1,12 +1,3 @@ - # 공항 데이터 표시 [SQLite](https://sqlite.org/index.html)를 기반으로 구축된 [데이터베이스](https://raw.githubusercontent.com/Microsoft/Data-Science-For-Beginners/main/2-Working-With-Data/05-relational-databases/airports.db)가 제공되었으며, 이 데이터베이스에는 공항에 대한 정보가 포함되어 있습니다. 아래에 스키마가 표시되어 있습니다. [Visual Studio Code](https://code.visualstudio.com?WT.mc_id=academic-77958-bethanycheum)에서 [SQLite 확장](https://marketplace.visualstudio.com/items?itemName=alexcvzz.vscode-sqlite&WT.mc_id=academic-77958-bethanycheum)을 사용하여 다양한 도시의 공항 정보를 표시합니다. diff --git a/translations/ko/2-Working-With-Data/06-non-relational/README.md b/translations/ko/2-Working-With-Data/06-non-relational/README.md index 1ccdb3e8..461f0e09 100644 --- a/translations/ko/2-Working-With-Data/06-non-relational/README.md +++ b/translations/ko/2-Working-With-Data/06-non-relational/README.md @@ -1,12 +1,3 @@ - # 데이터 작업: 비관계형 데이터 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/06-NoSQL.png)| diff --git a/translations/ko/2-Working-With-Data/06-non-relational/assignment.md b/translations/ko/2-Working-With-Data/06-non-relational/assignment.md index 58005201..1f49df53 100644 --- a/translations/ko/2-Working-With-Data/06-non-relational/assignment.md +++ b/translations/ko/2-Working-With-Data/06-non-relational/assignment.md @@ -1,12 +1,3 @@ - # 소다 수익 ## 지침 diff --git a/translations/ko/2-Working-With-Data/07-python/README.md b/translations/ko/2-Working-With-Data/07-python/README.md index 52fd7a9b..50926949 100644 --- a/translations/ko/2-Working-With-Data/07-python/README.md +++ b/translations/ko/2-Working-With-Data/07-python/README.md @@ -1,12 +1,3 @@ - # 데이터 작업: Python과 Pandas 라이브러리 | ![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/07-WorkWithPython.png) | diff --git a/translations/ko/2-Working-With-Data/07-python/assignment.md b/translations/ko/2-Working-With-Data/07-python/assignment.md index d42ed9c8..a9b5def4 100644 --- a/translations/ko/2-Working-With-Data/07-python/assignment.md +++ b/translations/ko/2-Working-With-Data/07-python/assignment.md @@ -1,12 +1,3 @@ - # 파이썬을 활용한 데이터 처리 과제 이 과제에서는 우리가 도전 과제에서 개발하기 시작한 코드를 확장하여 작성해 보도록 하겠습니다. 과제는 두 부분으로 구성되어 있습니다: diff --git a/translations/ko/2-Working-With-Data/08-data-preparation/README.md b/translations/ko/2-Working-With-Data/08-data-preparation/README.md index ce8127ad..3d84ceeb 100644 --- a/translations/ko/2-Working-With-Data/08-data-preparation/README.md +++ b/translations/ko/2-Working-With-Data/08-data-preparation/README.md @@ -1,12 +1,3 @@ - # 데이터 작업: 데이터 준비 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/08-DataPreparation.png)| diff --git a/translations/ko/2-Working-With-Data/08-data-preparation/assignment.md b/translations/ko/2-Working-With-Data/08-data-preparation/assignment.md index ac970152..64b50d84 100644 --- a/translations/ko/2-Working-With-Data/08-data-preparation/assignment.md +++ b/translations/ko/2-Working-With-Data/08-data-preparation/assignment.md @@ -1,12 +1,3 @@ - # 양식 데이터 평가 클라이언트가 고객 기반에 대한 기본 데이터를 수집하기 위해 [작은 양식](../../../../2-Working-With-Data/08-data-preparation/index.html)을 테스트했습니다. 그들은 수집한 데이터를 검증하기 위해 당신에게 가져왔습니다. 브라우저에서 `index.html` 페이지를 열어 양식을 확인할 수 있습니다. diff --git a/translations/ko/2-Working-With-Data/README.md b/translations/ko/2-Working-With-Data/README.md index c975a64a..1c925c0a 100644 --- a/translations/ko/2-Working-With-Data/README.md +++ b/translations/ko/2-Working-With-Data/README.md @@ -1,12 +1,3 @@ - # 데이터 작업하기 ![data love](../../../translated_images/ko/data-love.a22ef29e6742c852505ada062920956d3d7604870b281a8ca7c7ac6f37381d5a.jpg) diff --git a/translations/ko/3-Data-Visualization/09-visualization-quantities/README.md b/translations/ko/3-Data-Visualization/09-visualization-quantities/README.md index ec942deb..61c7f49e 100644 --- a/translations/ko/3-Data-Visualization/09-visualization-quantities/README.md +++ b/translations/ko/3-Data-Visualization/09-visualization-quantities/README.md @@ -1,12 +1,3 @@ - # 양의 시각화 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/09-Visualizing-Quantities.png)| diff --git a/translations/ko/3-Data-Visualization/09-visualization-quantities/assignment.md b/translations/ko/3-Data-Visualization/09-visualization-quantities/assignment.md index 66ad0ab5..a5dadcea 100644 --- a/translations/ko/3-Data-Visualization/09-visualization-quantities/assignment.md +++ b/translations/ko/3-Data-Visualization/09-visualization-quantities/assignment.md @@ -1,12 +1,3 @@ - # 선, 산점도, 막대 그래프 ## 지침 diff --git a/translations/ko/3-Data-Visualization/10-visualization-distributions/README.md b/translations/ko/3-Data-Visualization/10-visualization-distributions/README.md index c8ae0dab..b46b5c9e 100644 --- a/translations/ko/3-Data-Visualization/10-visualization-distributions/README.md +++ b/translations/ko/3-Data-Visualization/10-visualization-distributions/README.md @@ -1,12 +1,3 @@ - # 분포 시각화 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/10-Visualizing-Distributions.png)| diff --git a/translations/ko/3-Data-Visualization/10-visualization-distributions/assignment.md b/translations/ko/3-Data-Visualization/10-visualization-distributions/assignment.md index 871227ba..511b62fc 100644 --- a/translations/ko/3-Data-Visualization/10-visualization-distributions/assignment.md +++ b/translations/ko/3-Data-Visualization/10-visualization-distributions/assignment.md @@ -1,12 +1,3 @@ - # 기술을 적용해보세요 ## 지침 diff --git a/translations/ko/3-Data-Visualization/11-visualization-proportions/README.md b/translations/ko/3-Data-Visualization/11-visualization-proportions/README.md index c527a76c..5faccf2d 100644 --- a/translations/ko/3-Data-Visualization/11-visualization-proportions/README.md +++ b/translations/ko/3-Data-Visualization/11-visualization-proportions/README.md @@ -1,12 +1,3 @@ - # 비율 시각화 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/11-Visualizing-Proportions.png)| diff --git a/translations/ko/3-Data-Visualization/11-visualization-proportions/assignment.md b/translations/ko/3-Data-Visualization/11-visualization-proportions/assignment.md index 14a62ef5..92333b9d 100644 --- a/translations/ko/3-Data-Visualization/11-visualization-proportions/assignment.md +++ b/translations/ko/3-Data-Visualization/11-visualization-proportions/assignment.md @@ -1,12 +1,3 @@ - # 엑셀에서 시도해보기 ## 지침 diff --git a/translations/ko/3-Data-Visualization/12-visualization-relationships/README.md b/translations/ko/3-Data-Visualization/12-visualization-relationships/README.md index f4009473..947d7645 100644 --- a/translations/ko/3-Data-Visualization/12-visualization-relationships/README.md +++ b/translations/ko/3-Data-Visualization/12-visualization-relationships/README.md @@ -1,12 +1,3 @@ - # 관계 시각화: 꿀에 대한 모든 것 🍯 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/12-Visualizing-Relationships.png)| diff --git a/translations/ko/3-Data-Visualization/12-visualization-relationships/assignment.md b/translations/ko/3-Data-Visualization/12-visualization-relationships/assignment.md index 6b215bb4..6c984093 100644 --- a/translations/ko/3-Data-Visualization/12-visualization-relationships/assignment.md +++ b/translations/ko/3-Data-Visualization/12-visualization-relationships/assignment.md @@ -1,12 +1,3 @@ - # 벌집 속으로 뛰어들기 ## 지침 diff --git a/translations/ko/3-Data-Visualization/13-meaningful-visualizations/README.md b/translations/ko/3-Data-Visualization/13-meaningful-visualizations/README.md index 8812afe3..b52a2623 100644 --- a/translations/ko/3-Data-Visualization/13-meaningful-visualizations/README.md +++ b/translations/ko/3-Data-Visualization/13-meaningful-visualizations/README.md @@ -1,12 +1,3 @@ - # 의미 있는 데이터 시각화 만들기 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/13-MeaningfulViz.png)| diff --git a/translations/ko/3-Data-Visualization/13-meaningful-visualizations/assignment.md b/translations/ko/3-Data-Visualization/13-meaningful-visualizations/assignment.md index ad2ffd16..49b05c4a 100644 --- a/translations/ko/3-Data-Visualization/13-meaningful-visualizations/assignment.md +++ b/translations/ko/3-Data-Visualization/13-meaningful-visualizations/assignment.md @@ -1,12 +1,3 @@ - # 나만의 커스텀 시각화 만들기 ## 지침 diff --git a/translations/ko/3-Data-Visualization/13-meaningful-visualizations/solution/README.md b/translations/ko/3-Data-Visualization/13-meaningful-visualizations/solution/README.md index ab79aeea..7e2014d2 100644 --- a/translations/ko/3-Data-Visualization/13-meaningful-visualizations/solution/README.md +++ b/translations/ko/3-Data-Visualization/13-meaningful-visualizations/solution/README.md @@ -1,12 +1,3 @@ - # 위험한 관계 데이터 시각화 프로젝트 시작하려면, NPM과 Node가 컴퓨터에서 실행되고 있는지 확인해야 합니다. 의존성을 설치한 후(npm install), 프로젝트를 로컬에서 실행하세요(npm run serve): diff --git a/translations/ko/3-Data-Visualization/13-meaningful-visualizations/starter/README.md b/translations/ko/3-Data-Visualization/13-meaningful-visualizations/starter/README.md index 8d60bda7..ecf556e5 100644 --- a/translations/ko/3-Data-Visualization/13-meaningful-visualizations/starter/README.md +++ b/translations/ko/3-Data-Visualization/13-meaningful-visualizations/starter/README.md @@ -1,12 +1,3 @@ - # 위험한 관계 데이터 시각화 프로젝트 시작하려면, NPM과 Node가 컴퓨터에서 실행되고 있는지 확인해야 합니다. 의존성을 설치한 후(npm install), 프로젝트를 로컬에서 실행하세요(npm run serve): diff --git a/translations/ko/3-Data-Visualization/R/09-visualization-quantities/README.md b/translations/ko/3-Data-Visualization/R/09-visualization-quantities/README.md index 68612620..b99337ba 100644 --- a/translations/ko/3-Data-Visualization/R/09-visualization-quantities/README.md +++ b/translations/ko/3-Data-Visualization/R/09-visualization-quantities/README.md @@ -1,12 +1,3 @@ - # 수량 시각화 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/sketchnotes/09-Visualizing-Quantities.png)| |:---:| diff --git a/translations/ko/3-Data-Visualization/R/09-visualization-quantities/assignment.md b/translations/ko/3-Data-Visualization/R/09-visualization-quantities/assignment.md index 038e7b02..ffce7148 100644 --- a/translations/ko/3-Data-Visualization/R/09-visualization-quantities/assignment.md +++ b/translations/ko/3-Data-Visualization/R/09-visualization-quantities/assignment.md @@ -1,12 +1,3 @@ - # 선, 산점도, 막대 그래프 ## 지침 diff --git a/translations/ko/3-Data-Visualization/R/10-visualization-distributions/README.md b/translations/ko/3-Data-Visualization/R/10-visualization-distributions/README.md index 7513bcbb..f865081b 100644 --- a/translations/ko/3-Data-Visualization/R/10-visualization-distributions/README.md +++ b/translations/ko/3-Data-Visualization/R/10-visualization-distributions/README.md @@ -1,12 +1,3 @@ - # 분포 시각화 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/sketchnotes/10-Visualizing-Distributions.png)| diff --git a/translations/ko/3-Data-Visualization/R/10-visualization-distributions/assignment.md b/translations/ko/3-Data-Visualization/R/10-visualization-distributions/assignment.md index e97e27d7..d1a02477 100644 --- a/translations/ko/3-Data-Visualization/R/10-visualization-distributions/assignment.md +++ b/translations/ko/3-Data-Visualization/R/10-visualization-distributions/assignment.md @@ -1,12 +1,3 @@ - # 기술을 적용해보세요 ## 지침 diff --git a/translations/ko/3-Data-Visualization/R/11-visualization-proportions/README.md b/translations/ko/3-Data-Visualization/R/11-visualization-proportions/README.md index 8a294785..49994787 100644 --- a/translations/ko/3-Data-Visualization/R/11-visualization-proportions/README.md +++ b/translations/ko/3-Data-Visualization/R/11-visualization-proportions/README.md @@ -1,12 +1,3 @@ - # 비율 시각화 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../../sketchnotes/11-Visualizing-Proportions.png)| diff --git a/translations/ko/3-Data-Visualization/R/12-visualization-relationships/README.md b/translations/ko/3-Data-Visualization/R/12-visualization-relationships/README.md index 385e4b71..9faa82ec 100644 --- a/translations/ko/3-Data-Visualization/R/12-visualization-relationships/README.md +++ b/translations/ko/3-Data-Visualization/R/12-visualization-relationships/README.md @@ -1,12 +1,3 @@ - # 관계 시각화: 꿀에 대한 모든 것 🍯 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../../sketchnotes/12-Visualizing-Relationships.png)| diff --git a/translations/ko/3-Data-Visualization/R/13-meaningful-vizualizations/README.md b/translations/ko/3-Data-Visualization/R/13-meaningful-vizualizations/README.md index d22652ce..5b2f3043 100644 --- a/translations/ko/3-Data-Visualization/R/13-meaningful-vizualizations/README.md +++ b/translations/ko/3-Data-Visualization/R/13-meaningful-vizualizations/README.md @@ -1,12 +1,3 @@ - # 의미 있는 시각화 만들기 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../../sketchnotes/13-MeaningfulViz.png)| diff --git a/translations/ko/3-Data-Visualization/README.md b/translations/ko/3-Data-Visualization/README.md index 817c34e5..60594b2f 100644 --- a/translations/ko/3-Data-Visualization/README.md +++ b/translations/ko/3-Data-Visualization/README.md @@ -1,12 +1,3 @@ - # 시각화 ![라벤더 꽃 위의 벌](../../../translated_images/ko/bee.0aa1d91132b12e3a8994b9ca12816d05ce1642010d9b8be37f8d37365ba845cf.jpg) diff --git a/translations/ko/4-Data-Science-Lifecycle/14-Introduction/README.md b/translations/ko/4-Data-Science-Lifecycle/14-Introduction/README.md index 459dad0a..78f3d62f 100644 --- a/translations/ko/4-Data-Science-Lifecycle/14-Introduction/README.md +++ b/translations/ko/4-Data-Science-Lifecycle/14-Introduction/README.md @@ -1,12 +1,3 @@ - # 데이터 과학 생애 주기 소개 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/14-DataScience-Lifecycle.png)| diff --git a/translations/ko/4-Data-Science-Lifecycle/14-Introduction/assignment.md b/translations/ko/4-Data-Science-Lifecycle/14-Introduction/assignment.md index 8bad9845..729c340b 100644 --- a/translations/ko/4-Data-Science-Lifecycle/14-Introduction/assignment.md +++ b/translations/ko/4-Data-Science-Lifecycle/14-Introduction/assignment.md @@ -1,12 +1,3 @@ - # 데이터셋 평가하기 한 고객이 뉴욕시에서 택시 고객의 계절별 소비 습관을 조사하는 데 도움을 요청했습니다. diff --git a/translations/ko/4-Data-Science-Lifecycle/15-analyzing/README.md b/translations/ko/4-Data-Science-Lifecycle/15-analyzing/README.md index ffea4c54..99b80be9 100644 --- a/translations/ko/4-Data-Science-Lifecycle/15-analyzing/README.md +++ b/translations/ko/4-Data-Science-Lifecycle/15-analyzing/README.md @@ -1,12 +1,3 @@ - # 데이터 과학 생명주기: 분석하기 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/15-Analyzing.png)| diff --git a/translations/ko/4-Data-Science-Lifecycle/15-analyzing/assignment.md b/translations/ko/4-Data-Science-Lifecycle/15-analyzing/assignment.md index 23ca3251..2db57b66 100644 --- a/translations/ko/4-Data-Science-Lifecycle/15-analyzing/assignment.md +++ b/translations/ko/4-Data-Science-Lifecycle/15-analyzing/assignment.md @@ -1,12 +1,3 @@ - # 답을 탐구하기 이 문서는 이전 수업의 [과제](../14-Introduction/assignment.md)에서 이어지는 내용으로, 데이터 세트를 간단히 살펴본 바 있습니다. 이제 데이터를 더 깊이 분석해 보겠습니다. diff --git a/translations/ko/4-Data-Science-Lifecycle/16-communication/README.md b/translations/ko/4-Data-Science-Lifecycle/16-communication/README.md index dd4040dc..d3c5bb48 100644 --- a/translations/ko/4-Data-Science-Lifecycle/16-communication/README.md +++ b/translations/ko/4-Data-Science-Lifecycle/16-communication/README.md @@ -1,12 +1,3 @@ - # 데이터 과학 생명주기: 커뮤니케이션 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev)](../../sketchnotes/16-Communicating.png)| diff --git a/translations/ko/4-Data-Science-Lifecycle/16-communication/assignment.md b/translations/ko/4-Data-Science-Lifecycle/16-communication/assignment.md index 76d61a3e..d8b56017 100644 --- a/translations/ko/4-Data-Science-Lifecycle/16-communication/assignment.md +++ b/translations/ko/4-Data-Science-Lifecycle/16-communication/assignment.md @@ -1,12 +1,3 @@ - # 이야기를 만들어보세요 ## 지침 diff --git a/translations/ko/4-Data-Science-Lifecycle/README.md b/translations/ko/4-Data-Science-Lifecycle/README.md index acdfd494..dc3a1a41 100644 --- a/translations/ko/4-Data-Science-Lifecycle/README.md +++ b/translations/ko/4-Data-Science-Lifecycle/README.md @@ -1,12 +1,3 @@ - # 데이터 과학 생명주기 ![communication](../../../translated_images/ko/communication.06d8e2a88d30d168d661ad9f9f0a4f947ebff3719719cfdaf9ed00a406a01ead.jpg) diff --git a/translations/ko/5-Data-Science-In-Cloud/17-Introduction/README.md b/translations/ko/5-Data-Science-In-Cloud/17-Introduction/README.md index dcda344d..c41efdb7 100644 --- a/translations/ko/5-Data-Science-In-Cloud/17-Introduction/README.md +++ b/translations/ko/5-Data-Science-In-Cloud/17-Introduction/README.md @@ -1,12 +1,3 @@ - # 클라우드에서의 데이터 과학 소개 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/17-DataScience-Cloud.png)| diff --git a/translations/ko/5-Data-Science-In-Cloud/17-Introduction/assignment.md b/translations/ko/5-Data-Science-In-Cloud/17-Introduction/assignment.md index 34b8bcea..0938ff2f 100644 --- a/translations/ko/5-Data-Science-In-Cloud/17-Introduction/assignment.md +++ b/translations/ko/5-Data-Science-In-Cloud/17-Introduction/assignment.md @@ -1,12 +1,3 @@ - # 시장 조사 ## 지침 diff --git a/translations/ko/5-Data-Science-In-Cloud/18-Low-Code/README.md b/translations/ko/5-Data-Science-In-Cloud/18-Low-Code/README.md index 57b5f54c..f8743c39 100644 --- a/translations/ko/5-Data-Science-In-Cloud/18-Low-Code/README.md +++ b/translations/ko/5-Data-Science-In-Cloud/18-Low-Code/README.md @@ -1,12 +1,3 @@ - # 클라우드에서의 데이터 과학: "로우 코드/노 코드" 방식 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/18-DataScience-Cloud.png)| diff --git a/translations/ko/5-Data-Science-In-Cloud/18-Low-Code/assignment.md b/translations/ko/5-Data-Science-In-Cloud/18-Low-Code/assignment.md index fb96f2c0..48912ce9 100644 --- a/translations/ko/5-Data-Science-In-Cloud/18-Low-Code/assignment.md +++ b/translations/ko/5-Data-Science-In-Cloud/18-Low-Code/assignment.md @@ -1,12 +1,3 @@ - # Azure ML에서 저코드/무코드 방식으로 데이터 과학 프로젝트 수행하기 ## 지침 diff --git a/translations/ko/5-Data-Science-In-Cloud/19-Azure/README.md b/translations/ko/5-Data-Science-In-Cloud/19-Azure/README.md index cb6c73bc..0ac77f75 100644 --- a/translations/ko/5-Data-Science-In-Cloud/19-Azure/README.md +++ b/translations/ko/5-Data-Science-In-Cloud/19-Azure/README.md @@ -1,12 +1,3 @@ - # 클라우드에서의 데이터 과학: "Azure ML SDK" 방식 |![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/19-DataScience-Cloud.png)| diff --git a/translations/ko/5-Data-Science-In-Cloud/19-Azure/assignment.md b/translations/ko/5-Data-Science-In-Cloud/19-Azure/assignment.md index c503c5f2..77bfff13 100644 --- a/translations/ko/5-Data-Science-In-Cloud/19-Azure/assignment.md +++ b/translations/ko/5-Data-Science-In-Cloud/19-Azure/assignment.md @@ -1,12 +1,3 @@ - # Azure ML SDK를 사용한 데이터 과학 프로젝트 ## 지침 diff --git a/translations/ko/5-Data-Science-In-Cloud/README.md b/translations/ko/5-Data-Science-In-Cloud/README.md index 5fe6cccf..35fa5fbb 100644 --- a/translations/ko/5-Data-Science-In-Cloud/README.md +++ b/translations/ko/5-Data-Science-In-Cloud/README.md @@ -1,12 +1,3 @@ - # 클라우드에서의 데이터 과학 ![cloud-picture](../../../translated_images/ko/cloud-picture.f5526de3c6c6387b2d656ba94f019b3352e5e3854a78440e4fb00c93e2dea675.jpg) diff --git a/translations/ko/6-Data-Science-In-Wild/20-Real-World-Examples/README.md b/translations/ko/6-Data-Science-In-Wild/20-Real-World-Examples/README.md index 66b9c4d2..345fd2e7 100644 --- a/translations/ko/6-Data-Science-In-Wild/20-Real-World-Examples/README.md +++ b/translations/ko/6-Data-Science-In-Wild/20-Real-World-Examples/README.md @@ -1,12 +1,3 @@ - # 현실 세계의 데이터 과학 | ![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/20-DataScience-RealWorld.png) | diff --git a/translations/ko/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md b/translations/ko/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md index fb0261e4..66fe3f3f 100644 --- a/translations/ko/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md +++ b/translations/ko/6-Data-Science-In-Wild/20-Real-World-Examples/assignment.md @@ -1,12 +1,3 @@ - # 행성 컴퓨터 데이터셋 탐색하기 ## 지침 diff --git a/translations/ko/6-Data-Science-In-Wild/README.md b/translations/ko/6-Data-Science-In-Wild/README.md index c0c94c8a..03cebabe 100644 --- a/translations/ko/6-Data-Science-In-Wild/README.md +++ b/translations/ko/6-Data-Science-In-Wild/README.md @@ -1,12 +1,3 @@ - # 야생에서의 데이터 과학 산업 전반에 걸친 데이터 과학의 실제 응용 사례. diff --git a/translations/ko/AGENTS.md b/translations/ko/AGENTS.md index eb658aee..7d86397d 100644 --- a/translations/ko/AGENTS.md +++ b/translations/ko/AGENTS.md @@ -1,12 +1,3 @@ - # AGENTS.md ## 프로젝트 개요 diff --git a/translations/ko/CODE_OF_CONDUCT.md b/translations/ko/CODE_OF_CONDUCT.md index 65853c4c..f2ba6840 100644 --- a/translations/ko/CODE_OF_CONDUCT.md +++ b/translations/ko/CODE_OF_CONDUCT.md @@ -1,12 +1,3 @@ - # Microsoft 오픈 소스 행동 강령 이 프로젝트는 [Microsoft 오픈 소스 행동 강령](https://opensource.microsoft.com/codeofconduct/)을 채택했습니다. diff --git a/translations/ko/CONTRIBUTING.md b/translations/ko/CONTRIBUTING.md index d4c01607..5dbc2d5e 100644 --- a/translations/ko/CONTRIBUTING.md +++ b/translations/ko/CONTRIBUTING.md @@ -1,12 +1,3 @@ - # 초보자를 위한 데이터 과학 기여하기 초보자를 위한 데이터 과학 커리큘럼에 관심을 가져주셔서 감사합니다! 커뮤니티의 기여를 환영합니다. diff --git a/translations/ko/INSTALLATION.md b/translations/ko/INSTALLATION.md index c2b632ac..52ceb608 100644 --- a/translations/ko/INSTALLATION.md +++ b/translations/ko/INSTALLATION.md @@ -1,12 +1,3 @@ - # 설치 가이드 이 가이드는 초보자를 위한 데이터 과학 커리큘럼을 작업할 수 있도록 환경을 설정하는 방법을 안내합니다. diff --git a/translations/ko/README.md b/translations/ko/README.md index e0bc1a06..5c5f939c 100644 --- a/translations/ko/README.md +++ b/translations/ko/README.md @@ -1,13 +1,4 @@ - -# 초보자를 위한 데이터 과학 - 교육 과정 +# 초보자를 위한 데이터 과학 - 커리큘럼 [![GitHub Codespaces에서 열기](https://github.com/codespaces/badge.svg)](https://github.com/codespaces/new?hide_repo_select=true&ref=main&repo=344191198) @@ -19,244 +10,244 @@ CO_OP_TRANSLATOR_METADATA: [![GitHub 감시자](https://img.shields.io/github/watchers/microsoft/Data-Science-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/Data-Science-For-Beginners/watchers/) [![GitHub 포크](https://img.shields.io/github/forks/microsoft/Data-Science-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/Data-Science-For-Beginners/network/) -[![GitHub 별](https://img.shields.io/github/stars/microsoft/Data-Science-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/Data-Science-For-Beginners/stargazers/) +[![GitHub 스타](https://img.shields.io/github/stars/microsoft/Data-Science-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/Data-Science-For-Beginners/stargazers/) [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) [![Microsoft Foundry 개발자 포럼](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) -마이크로소프트 Azure 클라우드 옹호자는 데이터 과학에 관한 10주, 20개의 수업 커리큘럼을 제공하게 되어 기쁩니다. 각 수업은 사전/사후 퀴즈, 수업 완료를 위한 서면 지침, 솔루션, 과제로 구성되어 있습니다. 프로젝트 기반 교수법을 통해 빌드하면서 학습할 수 있어 새로운 기술이 '잘 붙는' 입증된 방법입니다. +Microsoft의 Azure Cloud Advocates가 데이터 과학에 관한 10주 20강의 커리큘럼을 기쁜 마음으로 제공합니다. 각 강의는 사전 및 사후 퀴즈, 강의를 완료하기 위한 서면 지침, 해답 및 과제를 포함합니다. 프로젝트 기반 교육 방식을 통해 학습하면서 직접 만들어 보는 경험을 제공하며, 이는 새로운 기술을 확실히 익히는 검증된 방법입니다. **저자 여러분께 진심으로 감사드립니다:** [Jasmine Greenaway](https://www.twitter.com/paladique), [Dmitry Soshnikov](http://soshnikov.com), [Nitya Narasimhan](https://twitter.com/nitya), [Jalen McGee](https://twitter.com/JalenMcG), [Jen Looper](https://twitter.com/jenlooper), [Maud Levy](https://twitter.com/maudstweets), [Tiffany Souterre](https://twitter.com/TiffanySouterre), [Christopher Harrison](https://www.twitter.com/geektrainer). -**🙏 특별히 감사드립니다 🙏 [Microsoft Student Ambassador](https://studentambassadors.microsoft.com/) 저자, 검토자 및 콘텐츠 기여자 분들께,** 특히 Aaryan Arora, [Aditya Garg](https://github.com/AdityaGarg00), [Alondra Sanchez](https://www.linkedin.com/in/alondra-sanchez-molina/), [Ankita Singh](https://www.linkedin.com/in/ankitasingh007), [Anupam Mishra](https://www.linkedin.com/in/anupam--mishra/), [Arpita Das](https://www.linkedin.com/in/arpitadas01/), ChhailBihari Dubey, [Dibri Nsofor](https://www.linkedin.com/in/dibrinsofor), [Dishita Bhasin](https://www.linkedin.com/in/dishita-bhasin-7065281bb), [Majd Safi](https://www.linkedin.com/in/majd-s/), [Max Blum](https://www.linkedin.com/in/max-blum-6036a1186/), [Miguel Correa](https://www.linkedin.com/in/miguelmque/), [Mohamma Iftekher (Iftu) Ebne Jalal](https://twitter.com/iftu119), [Nawrin Tabassum](https://www.linkedin.com/in/nawrin-tabassum), [Raymond Wangsa Putra](https://www.linkedin.com/in/raymond-wp/), [Rohit Yadav](https://www.linkedin.com/in/rty2423), Samridhi Sharma, [Sanya Sinha](https://www.linkedin.com/mwlite/in/sanya-sinha-13aab1200), +**🙏 특별 감사드립니다 🙏 [Microsoft Student Ambassador](https://studentambassadors.microsoft.com/) 저자, 검토자 및 콘텐츠 기여자 여러분께,** 특히 Aaryan Arora, [Aditya Garg](https://github.com/AdityaGarg00), [Alondra Sanchez](https://www.linkedin.com/in/alondra-sanchez-molina/), [Ankita Singh](https://www.linkedin.com/in/ankitasingh007), [Anupam Mishra](https://www.linkedin.com/in/anupam--mishra/), [Arpita Das](https://www.linkedin.com/in/arpitadas01/), ChhailBihari Dubey, [Dibri Nsofor](https://www.linkedin.com/in/dibrinsofor), [Dishita Bhasin](https://www.linkedin.com/in/dishita-bhasin-7065281bb), [Majd Safi](https://www.linkedin.com/in/majd-s/), [Max Blum](https://www.linkedin.com/in/max-blum-6036a1186/), [Miguel Correa](https://www.linkedin.com/in/miguelmque/), [Mohamma Iftekher (Iftu) Ebne Jalal](https://twitter.com/iftu119), [Nawrin Tabassum](https://www.linkedin.com/in/nawrin-tabassum), [Raymond Wangsa Putra](https://www.linkedin.com/in/raymond-wp/), [Rohit Yadav](https://www.linkedin.com/in/rty2423), Samridhi Sharma, [Sanya Sinha](https://www.linkedin.com/mwlite/in/sanya-sinha-13aab1200), [Sheena Narula](https://www.linkedin.com/in/sheena-narua-n/), [Tauqeer Ahmad](https://www.linkedin.com/in/tauqeerahmad5201/), Yogendrasingh Pawar , [Vidushi Gupta](https://www.linkedin.com/in/vidushi-gupta07/), [Jasleen Sondhi](https://www.linkedin.com/in/jasleen-sondhi/) -|![@sketchthedocs의 스케치노트 https://sketchthedocs.dev](../../../../translated_images/ko/00-Title.8af36cd35da1ac55.webp)| +|![@sketchthedocs의 스케치노트 https://sketchthedocs.dev](../../translated_images/ko/00-Title.8af36cd35da1ac55.webp)| |:---:| -| 초보자를 위한 데이터 과학 - _[@nitya](https://twitter.com/nitya)의 스케치노트_ | +| 초보자를 위한 데이터 과학 - _[@nitya](https://twitter.com/nitya) 스케치노트_ | ### 🌐 다국어 지원 -#### GitHub Action을 통해 지원됨 (자동 및 항상 최신 상태 유지) +#### GitHub 액션을 통한 지원 (자동 및 항상 최신 상태 유지) -[Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](../hi/README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Korean](./README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../br/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) +[아랍어](../ar/README.md) | [벵골어](../bn/README.md) | [불가리아어](../bg/README.md) | [버마어 (미얀마)](../my/README.md) | [중국어 (간체)](../zh-CN/README.md) | [중국어 (번체, 홍콩)](../zh-HK/README.md) | [중국어 (번체, 마카오)](../zh-MO/README.md) | [중국어 (번체, 대만)](../zh-TW/README.md) | [크로아티아어](../hr/README.md) | [체코어](../cs/README.md) | [덴마크어](../da/README.md) | [네덜란드어](../nl/README.md) | [에스토니아어](../et/README.md) | [핀란드어](../fi/README.md) | [프랑스어](../fr/README.md) | [독일어](../de/README.md) | [그리스어](../el/README.md) | [히브리어](../he/README.md) | [힌디어](../hi/README.md) | [헝가리어](../hu/README.md) | [인도네시아어](../id/README.md) | [이탈리아어](../it/README.md) | [일본어](../ja/README.md) | [칸나다어](../kn/README.md) | [한국어](./README.md) | [리투아니아어](../lt/README.md) | [말레이어](../ms/README.md) | [말라얄람어](../ml/README.md) | [마라티어](../mr/README.md) | [네팔어](../ne/README.md) | [나이지리아 피진어](../pcm/README.md) | [노르웨이어](../no/README.md) | [페르시아어 (파르시)](../fa/README.md) | [폴란드어](../pl/README.md) | [포르투갈어 (브라질)](../pt-BR/README.md) | [포르투갈어 (포르투갈)](../pt-PT/README.md) | [펀자브어 (구르무키)](../pa/README.md) | [루마니아어](../ro/README.md) | [러시아어](../ru/README.md) | [세르비아어 (키릴 문자)](../sr/README.md) | [슬로바키아어](../sk/README.md) | [슬로베니아어](../sl/README.md) | [스페인어](../es/README.md) | [스와힐리어](../sw/README.md) | [스웨덴어](../sv/README.md) | [타갈로그어 (필리피노)](../tl/README.md) | [타밀어](../ta/README.md) | [텔루구어](../te/README.md) | [태국어](../th/README.md) | [터키어](../tr/README.md) | [우크라이나어](../uk/README.md) | [우르두어](../ur/README.md) | [베트남어](../vi/README.md) -> **로컬로 클론하는 것을 선호하십니까?** +> **로컬 복제를 선호하십니까?** -> 이 저장소에는 50개 이상의 언어 번역이 포함되어 있어 다운로드 크기가 크게 증가합니다. 번역 없이 클론하려면 희소 체크아웃을 사용하세요: +> 이 저장소에는 50개 이상의 언어 번역이 포함되어 있어 다운로드 크기가 상당히 증가합니다. 번역 없이 복제하려면 희소 체크아웃을 사용하세요: > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/Data-Science-For-Beginners.git > cd Data-Science-For-Beginners > git sparse-checkout set --no-cone '/*' '!translations' '!translated_images' > ``` -> 이를 통해 훨씬 빠른 다운로드로 수업을 완료하는 데 필요한 모든 자료를 얻을 수 있습니다. +> 이 방법으로 보다 빠른 다운로드 속도로 과정 완료에 필요한 모든 것을 얻을 수 있습니다. -**추가 언어 지원을 원하시면 [여기](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)에서 목록을 확인하세요** +**추가 번역 언어를 지원하고 싶다면 [여기](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)에서 확인하세요** -#### 커뮤니티에 참여하세요 +#### 커뮤니티에 참여하기 [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -우리는 Discord에서 AI와 함께하는 학습 시리즈를 진행 중이며, 2025년 9월 18일부터 30일까지 진행되는 [Learn with AI Series](https://aka.ms/learnwithai/discord)에서 자세한 정보를 얻고 참여할 수 있습니다. 여기에서 GitHub Copilot을 데이터 과학에 활용하는 팁과 요령을 얻을 수 있습니다. +우리는 Discord에서 AI와 함께 배우는 시리즈를 진행 중입니다. 자세한 내용을 확인하고 2025년 9월 18일부터 30일까지 [Learn with AI Series](https://aka.ms/learnwithai/discord)에 참여하세요. GitHub Copilot을 데이터 과학에 활용하는 팁과 요령을 얻을 수 있습니다. -![Learn with AI series](../../../../translated_images/ko/1.2b28cdc6205e26fe.webp) +![AI와 함께 배우기 시리즈](../../translated_images/ko/1.2b28cdc6205e26fe.webp) # 학생이신가요? -다음 자료로 시작하세요: +다음 리소스부터 시작하세요: -- [학생 허브 페이지](https://docs.microsoft.com/en-gb/learn/student-hub?WT.mc_id=academic-77958-bethanycheum) 이 페이지에는 초보자를 위한 자료, 학생 패키지, 무료 인증 바우처 획득 방법 등이 포함되어 있습니다. 콘텐츠가 적어도 매달 교체되므로 즐겨찾기해두고 수시로 확인하는 것이 좋습니다. -- [Microsoft Learn Student Ambassadors](https://studentambassadors.microsoft.com?WT.mc_id=academic-77958-bethanycheum) 전 세계 학생 대사 커뮤니티에 참여하여 Microsoft에 진입할 수 있는 기회를 얻으세요. +- [학생 허브 페이지](https://docs.microsoft.com/en-gb/learn/student-hub?WT.mc_id=academic-77958-bethanycheum) 이 페이지에서 초보자용 리소스, 학생 패키지, 무료 인증 바우처 받는 방법 등을 찾을 수 있습니다. 콘텐츠는 매월 변경되니 즐겨찾기에 추가하고 수시로 확인해 보세요. +- [Microsoft Learn Student Ambassadors](https://studentambassadors.microsoft.com?WT.mc_id=academic-77958-bethanycheum) 전 세계 학생 대사 커뮤니티에 참여하세요. 이것이 Microsoft로의 길이 될 수 있습니다. # 시작하기 ## 📚 문서 -- **[설치 가이드](INSTALLATION.md)** - 초보자를 위한 단계별 설치 지침 -- **[사용 가이드](USAGE.md)** - 예제 및 일반적인 작업 흐름 -- **[문제 해결](TROUBLESHOOTING.md)** - 일반 문제 해결 방법 -- **[기여 가이드](CONTRIBUTING.md)** - 프로젝트 기여 방법 -- **[교사용](for-teachers.md)** - 교육 지침 및 교실 자료 +- **[설치 가이드](INSTALLATION.md)** - 초보자를 위한 단계별 설치 안내 +- **[사용 가이드](USAGE.md)** - 예제와 일반적인 작업 흐름 +- **[문제 해결](TROUBLESHOOTING.md)** - 일반적인 문제 해결 방법 +- **[기여 가이드](CONTRIBUTING.md)** - 이 프로젝트에 기여하는 방법 +- **[교사용 자료](for-teachers.md)** - 교수법 및 교실용 자료 ## 👨‍🎓 학생용 -> **완전 초보자:** 데이터 과학이 처음인가요? [초보자 친화적 예제](examples/README.md)부터 시작하세요! 이 간단하고 주석이 잘 달린 예제를 통해 기본기를 이해한 뒤 전체 커리큘럼에 참여할 수 있습니다. -> **[학생](https://aka.ms/student-page):** 이 커리큘럼을 혼자서 사용하려면 전체 저장소를 포크한 뒤, 사전 강의 퀴즈부터 시작해 직접 문제를 해결하며 진행하세요. 강의를 읽고 나머지 활동을 완료하세요. 솔루션 코드를 복사하기보다는 수업 내용을 이해하고 직접 프로젝트를 만들어보는 것을 추천합니다. 각 프로젝트 중심의 수업별로 /solutions 폴더에 솔루션 코드가 제공됩니다. 또 다른 방법으로는 친구들과 스터디 그룹을 구성해 함께 콘텐츠를 학습하는 것입니다. 더 심도 있는 학습을 위해 [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/qprpajyoy3x0g7?WT.mc_id=academic-77958-bethanycheum)을 권장합니다. +> **완전 초보자**: 데이터 과학이 처음이라면, [초보자 친화적 예제](examples/README.md)부터 시작하세요! 이 간단하고 주석이 잘 달린 예제들은 전체 커리큘럼에 들어가기 전 기본기를 이해하는 데 도움을 줍니다. +> **[학생](https://aka.ms/student-page)**: 이 커리큘럼을 스스로 사용하려면, 전체 저장소를 포크한 뒤 사전 강의 퀴즈부터 시작해 보세요. 그 다음 강의를 읽고 나머지 활동을 완성하세요. 해답 코드를 단순히 복사하지 말고 강의를 이해하며 프로젝트를 만들어 보세요. 해답 코드는 각 프로젝트 중심 강의의 /solutions 폴더에 있습니다. 또 다른 방법은 친구들과 스터디 그룹을 만들어 함께 내용을 진행하는 것입니다. 더 깊이 공부하고 싶다면 [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/qprpajyoy3x0g7?WT.mc_id=academic-77958-bethanycheum)을 추천합니다. -**빠른 시작:** +**빠른 시작 방법:** 1. 환경 설정을 위해 [설치 가이드](INSTALLATION.md)를 확인하세요 -2. 커리큘럼 작업 방법을 배우기 위해 [사용 가이드](USAGE.md)를 검토하세요 -3. 1과부터 시작해 순서대로 진행하세요 -4. 지원을 위해 [Discord 커뮤니티](https://aka.ms/ds4beginners/discord)에 참여하세요 +2. 커리큘럼 사용법을 배우려면 [사용 가이드](USAGE.md)를 검토하세요 +3. 1강부터 순서대로 시작하세요 +4. 지원이 필요하면 [Discord 커뮤니티](https://aka.ms/ds4beginners/discord)에 참여하세요 ## 👩‍🏫 교사용 -> **교사분들:** 이 커리큘럼 사용 방법에 관한 [제안사항](for-teachers.md)을 포함했습니다. 피드백을 [토론 포럼](https://github.com/microsoft/Data-Science-For-Beginners/discussions)에서 환영합니다! +> **교사분들께:** 이 커리큘럼 활용을 위한 [몇 가지 제안](for-teachers.md)을 포함했습니다. 여러분의 피드백을 [토론 포럼](https://github.com/microsoft/Data-Science-For-Beginners/discussions)에서 기다립니다! +## 팀을 소개합니다 -## 팀 소개 -[![프로모션 비디오](../../ds-for-beginners.gif)](https://youtu.be/8mzavjQSMM4 "프로모션 비디오") +[![프로모션 영상](../../ds-for-beginners.gif)](https://youtu.be/8mzavjQSMM4 "프로모션 영상") -**Gif 제작** [Mohit Jaisal](https://www.linkedin.com/in/mohitjaisal) +**GIF 제공자** [Mohit Jaisal](https://www.linkedin.com/in/mohitjaisal) -> 🎥 위 이미지를 클릭하면 이 프로젝트와 그것을 만든 분들에 관한 비디오를 볼 수 있습니다! +> 🎥 위 이미지를 클릭하면 프로젝트와 그것을 만든 사람들에 관한 영상을 볼 수 있습니다! -## 교육 철학 +## 교수법 -이 커리큘럼을 만들면서 두 가지 교육 원칙을 선택했습니다: 프로젝트 기반 학습 보장과 빈번한 퀴즈 포함입니다. 이 시리즈가 끝나면 학생들은 데이터 과학의 기본 원칙들, 윤리적 개념, 데이터 준비, 다양한 데이터 작업 방법, 데이터 시각화, 데이터 분석, 데이터 과학의 실제 사용 사례 등 다양한 내용을 배울 것입니다. +이 커리큘럼을 구성하면서 우리는 두 가지 교수 원칙을 선택했습니다: 프로젝트 기반 학습과 자주 출제되는 퀴즈 포함. 이 시리즈가 끝날 때쯤 학생들은 윤리 개념, 데이터 준비, 다양한 데이터 작업 방법, 데이터 시각화, 데이터 분석, 데이터 과학의 실제 사례 등 기본적인 데이터 과학 원리를 학습하게 됩니다. -또한 수업 전에 치르는 낮은 부담의 퀴즈는 학생들이 주제 학습에 집중하도록 동기를 부여하며, 수업 후의 두 번째 퀴즈는 학습 내용을 더욱 잘 기억하도록 도와줍니다. 이 커리큘럼은 유연하면서도 재미있게 설계되어 전체 또는 일부만 수강할 수 있습니다. 프로젝트는 처음에는 작은 규모로 시작하여 10주 과정이 끝날 때 쯤에는 점차 복잡해집니다. +또한, 수업 전에 진행하는 간단한 퀴즈는 주제 학습에 대한 의도를 세우고, 수업 후 두 번째 퀴즈는 학습 내용을 더 오래 기억하도록 돕습니다. 이 커리큘럼은 유연하고 재미있게 설계되었으며 전부 또는 일부만 학습할 수도 있습니다. 프로젝트는 작게 시작해 10주 주기 종료 시점에 점점 더 복잡해집니다. -> 저희 [행동 강령](CODE_OF_CONDUCT.md), [기여 안내](CONTRIBUTING.md), [번역 가이드](TRANSLATIONS.md)를 확인하세요. 건설적인 피드백을 환영합니다! +> 우리의 [행동 강령](CODE_OF_CONDUCT.md), [기여 가이드](CONTRIBUTING.md), [번역 가이드](TRANSLATIONS.md)를 확인하세요. 건설적인 피드백을 환영합니다! ## 각 수업에는 다음이 포함됩니다: - 선택적 스케치노트 -- 선택적 보조 비디오 +- 선택적 추가 영상 - 수업 전 워밍업 퀴즈 -- 서면 수업 자료 -- 프로젝트 기반 수업의 경우, 프로젝트를 만드는 단계별 가이드 +- 작성된 강의 내용 +- 프로젝트 기반 수업의 경우 프로젝트를 단계별로 만드는 가이드 - 지식 점검 - 도전 과제 -- 보충 읽을거리 +- 추가 읽을거리 - 과제 - [수업 후 퀴즈](https://ff-quizzes.netlify.app/en/) -> **퀴즈에 대한 안내**: 모든 퀴즈는 Quiz-App 폴더에 포함되어 있으며, 총 40개의 퀴즈가 각 3문항으로 구성되어 있습니다. 수업 내에서 링크되어 있지만, 퀴즈 앱은 로컬에서 실행하거나 Azure에 배포할 수 있으며 `quiz-app` 폴더의 지침을 따르세요. 점진적으로 현지화 작업도 진행 중입니다. +> **퀴즈에 대한 참고**: 모든 퀴즈는 Quiz-App 폴더에 있으며 총 40개의 3문제 퀴즈로 구성되어 있습니다. 퀴즈는 수업 중 연결되어 있지만 퀴즈 앱을 로컬에서 실행하거나 Azure에 배포할 수도 있습니다. `quiz-app` 폴더 내의 지침을 따르세요. 점차 현지화되고 있습니다. ## 🎓 초보자 친화적 예제 -**데이터 과학이 처음인가요?** 시작하는 데 도움을 주는 간단하고 주석이 잘 달린 코드가 담긴 특별한 [예제 디렉터리](examples/README.md)를 만들었습니다: +**데이터 과학이 처음이신가요?** 저희가 간단하고 주석이 잘 달린 코드를 모은 특별한 [예제 디렉터리](examples/README.md)를 만들었습니다: - 🌟 **Hello World** - 첫 데이터 과학 프로그램 -- 📂 **데이터 불러오기** - 데이터셋 읽기 및 탐색 배우기 +- 📂 **데이터 불러오기** - 데이터셋 읽기와 탐색 배우기 - 📊 **간단한 분석** - 통계 계산과 패턴 찾기 - 📈 **기본 시각화** - 차트와 그래프 만들기 -- 🔬 **실제 프로젝트** - 시작부터 끝까지 완성하는 워크플로우 +- 🔬 **실제 프로젝트** - 시작부터 끝까지의 완전한 워크플로우 -각 예제에는 단계별로 자세한 주석이 포함되어 있어, 완전 초보자에게 적합합니다! +각 예제는 모든 단계를 자세히 설명하는 주석이 포함되어 있어 완전 초보자에게 안성맞춤입니다! -👉 **[예제부터 시작하기](examples/README.md)** 👈 +👉 **[예제부터 시작하세요](examples/README.md)** 👈 ## 수업 목록 -|![ @sketchthedocs https://sketchthedocs.dev 제공 스케치노트](../../../../translated_images/ko/00-Roadmap.4905d6567dff4753.webp)| +|![ @sketchthedocs 제공 스케치노트 https://sketchthedocs.dev](../../translated_images/ko/00-Roadmap.4905d6567dff4753.webp)| |:---:| -| 데이터 과학 초보자를 위한 로드맵 - _[nitya](https://twitter.com/nitya) 작성 스케치노트_ | +| 초보자용 데이터 과학 로드맵 - _스케치노트 작성자 [@nitya](https://twitter.com/nitya)_ | | 수업 번호 | 주제 | 수업 그룹 | 학습 목표 | 링크된 수업 | 저자 | | :-----------: | :----------------------------------------: | :--------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------: | :----: | -| 01 | 데이터 과학 정의 | [소개](1-Introduction/README.md) | 데이터 과학의 기본 개념과 인공지능, 머신러닝, 빅데이터와의 관계를 학습합니다. | [수업](1-Introduction/01-defining-data-science/README.md) [비디오](https://youtu.be/beZ7Mb_oz9I) | [Dmitry](http://soshnikov.com) | -| 02 | 데이터 과학 윤리 | [소개](1-Introduction/README.md) | 데이터 윤리 개념, 도전 과제 및 프레임워크. | [수업](1-Introduction/02-ethics/README.md) | [Nitya](https://twitter.com/nitya) | -| 03 | 데이터 정의 | [소개](1-Introduction/README.md) | 데이터 분류 방법과 일반적인 출처. | [수업](1-Introduction/03-defining-data/README.md) | [Jasmine](https://www.twitter.com/paladique) | -| 04 | 통계 및 확률 입문 | [소개](1-Introduction/README.md) | 데이터를 이해하기 위한 확률 및 통계의 수학적 기법. | [수업](1-Introduction/04-stats-and-probability/README.md) [비디오](https://youtu.be/Z5Zy85g4Yjw) | [Dmitry](http://soshnikov.com) | -| 05 | 관계형 데이터 다루기 | [데이터 다루기](2-Working-With-Data/README.md) | 관계형 데이터 소개 및 SQL(발음: 씨퀄)을 사용해 관계형 데이터를 탐색하고 분석하는 기초. | [수업](2-Working-With-Data/05-relational-databases/README.md) | [Christopher](https://www.twitter.com/geektrainer) | | | -| 06 | NoSQL 데이터 다루기 | [데이터 다루기](2-Working-With-Data/README.md) | 비관계형 데이터 소개, 다양한 유형 및 문서형 데이터베이스 탐색과 분석 기본. | [수업](2-Working-With-Data/06-non-relational/README.md) | [Jasmine](https://twitter.com/paladique)| -| 07 | Python 작업 | [데이터 다루기](2-Working-With-Data/README.md) | Pandas 같은 라이브러리를 활용한 데이터 탐색에 필요한 Python 기본 사항. Python 프로그래밍 기초 이해 추천. | [수업](2-Working-With-Data/07-python/README.md) [비디오](https://youtu.be/dZjWOGbsN4Y) | [Dmitry](http://soshnikov.com) | -| 08 | 데이터 준비 | [데이터 다루기](2-Working-With-Data/README.md) | 누락되었거나 부정확하거나 불완전한 데이터를 처리하기 위한 데이터 정제 및 변환 기술 주제. | [수업](2-Working-With-Data/08-data-preparation/README.md) | [Jasmine](https://www.twitter.com/paladique) | -| 09 | 양 시각화 | [데이터 시각화](3-Data-Visualization/README.md) | Matplotlib를 사용해 새 데이터를 시각화하는 방법 배우기 🦆 | [수업](3-Data-Visualization/09-visualization-quantities/README.md) | [Jen](https://twitter.com/jenlooper) | -| 10 | 데이터 분포 시각화 | [데이터 시각화](3-Data-Visualization/README.md) | 구간 내 관측값과 추세 시각화. | [수업](3-Data-Visualization/10-visualization-distributions/README.md) | [Jen](https://twitter.com/jenlooper) | -| 11 | 비율 시각화 | [데이터 시각화](3-Data-Visualization/README.md) | 이산 및 그룹화된 백분율 시각화. | [수업](3-Data-Visualization/11-visualization-proportions/README.md) | [Jen](https://twitter.com/jenlooper) | -| 12 | 관계 시각화 | [데이터 시각화](3-Data-Visualization/README.md) | 데이터 세트와 변수 간 연결 및 상관관계 시각화. | [수업](3-Data-Visualization/12-visualization-relationships/README.md) | [Jen](https://twitter.com/jenlooper) | -| 13 | 의미 있는 시각화 | [데이터 시각화](3-Data-Visualization/README.md) | 효과적 문제 해결과 통찰을 위한 가치 있는 시각화를 만드는 기법과 안내. | [수업](3-Data-Visualization/13-meaningful-visualizations/README.md) | [Jen](https://twitter.com/jenlooper) | -| 14 | 데이터 과학 라이프사이클 소개 | [라이프사이클](4-Data-Science-Lifecycle/README.md) | 데이터 과학 라이프사이클과 첫 단계인 데이터 수집 및 추출 소개. | [수업](4-Data-Science-Lifecycle/14-Introduction/README.md) | [Jasmine](https://twitter.com/paladique) | -| 15 | 분석하기 | [라이프사이클](4-Data-Science-Lifecycle/README.md) | 데이터 과학 라이프사이클의 이 단계는 데이터를 분석하는 기술에 집중합니다. | [수업](4-Data-Science-Lifecycle/15-analyzing/README.md) | [Jasmine](https://twitter.com/paladique) | | | -| 16 | 커뮤니케이션 | [라이프사이클](4-Data-Science-Lifecycle/README.md) | 데이터 과학 라이프사이클의 이 단계는 의사결정자가 쉽게 이해할 수 있도록 데이터로부터 도출된 통찰을 전달하는 데 집중합니다. | [수업](4-Data-Science-Lifecycle/16-communication/README.md) | [Jalen](https://twitter.com/JalenMcG) | | | -| 17 | 클라우드에서의 데이터 과학 | [클라우드 데이터](5-Data-Science-In-Cloud/README.md) | 클라우드에서의 데이터 과학과 그 이점을 소개하는 시리즈. | [수업](5-Data-Science-In-Cloud/17-Introduction/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) | -| 18 | 클라우드에서의 데이터 과학 | [클라우드 데이터](5-Data-Science-In-Cloud/README.md) | 로우 코드 도구를 사용한 모델 학습. |[수업](5-Data-Science-In-Cloud/18-Low-Code/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) | -| 19 | 클라우드에서의 데이터 과학 | [클라우드 데이터](5-Data-Science-In-Cloud/README.md) | Azure Machine Learning Studio를 이용한 모델 배포. | [수업](5-Data-Science-In-Cloud/19-Azure/README.md)| [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) | -| 20 | 현장 데이터 과학 | [현장](6-Data-Science-In-Wild/README.md) | 실제 세계에서의 데이터 과학 기반 프로젝트. | [수업](6-Data-Science-In-Wild/20-Real-World-Examples/README.md) | [Nitya](https://twitter.com/nitya) | +| 01 | 데이터 과학 정의 | [소개](1-Introduction/README.md) | 데이터 과학의 기본 개념과 인공지능, 기계 학습, 빅 데이터와의 관련성 배우기. | [강의](1-Introduction/01-defining-data-science/README.md) [영상](https://youtu.be/beZ7Mb_oz9I) | [Dmitry](http://soshnikov.com) | +| 02 | 데이터 과학 윤리 | [소개](1-Introduction/README.md) | 데이터 윤리 개념, 도전 과제 및 프레임워크. | [강의](1-Introduction/02-ethics/README.md) | [Nitya](https://twitter.com/nitya) | +| 03 | 데이터 정의 | [소개](1-Introduction/README.md) | 데이터가 어떻게 분류되는지와 일반적인 출처. | [강의](1-Introduction/03-defining-data/README.md) | [Jasmine](https://www.twitter.com/paladique) | +| 04 | 통계 및 확률 소개 | [소개](1-Introduction/README.md) | 데이터를 이해하기 위한 확률 및 통계의 수학적 기법. | [강의](1-Introduction/04-stats-and-probability/README.md) [영상](https://youtu.be/Z5Zy85g4Yjw) | [Dmitry](http://soshnikov.com) | +| 05 | 관계형 데이터 다루기 | [데이터 작업](2-Working-With-Data/README.md) | 관계형 데이터 소개와 SQL(“see-quell”로 발음)로 관계형 데이터를 탐색하고 분석하는 기본. | [강의](2-Working-With-Data/05-relational-databases/README.md) | [Christopher](https://www.twitter.com/geektrainer) | | | +| 06 | NoSQL 데이터 다루기 | [데이터 작업](2-Working-With-Data/README.md) | 비관계형 데이터, 다양한 유형 및 문서 데이터베이스 탐색과 기본 분석법 소개. | [강의](2-Working-With-Data/06-non-relational/README.md) | [Jasmine](https://twitter.com/paladique)| +| 07 | Python 다루기 | [데이터 작업](2-Working-With-Data/README.md) | Pandas와 같은 라이브러리를 사용한 데이터 탐색 Python 기초. Python 프로그래밍 기초 지식 권장. | [강의](2-Working-With-Data/07-python/README.md) [영상](https://youtu.be/dZjWOGbsN4Y) | [Dmitry](http://soshnikov.com) | +| 08 | 데이터 준비 | [데이터 작업](2-Working-With-Data/README.md) | 누락되거나 부정확하거나 불완전한 데이터를 처리하기 위한 데이터 클리닝 및 변환 기법. | [강의](2-Working-With-Data/08-data-preparation/README.md) | [Jasmine](https://www.twitter.com/paladique) | +| 09 | 양적 데이터 시각화 | [데이터 시각화](3-Data-Visualization/README.md) | Matplotlib를 사용하여 새 데이터를 시각화하는 법 배우기 🦆 | [강의](3-Data-Visualization/09-visualization-quantities/README.md) | [Jen](https://twitter.com/jenlooper) | +| 10 | 데이터 분포 시각화 | [데이터 시각화](3-Data-Visualization/README.md) | 구간 내 관측치와 추세 시각화. | [강의](3-Data-Visualization/10-visualization-distributions/README.md) | [Jen](https://twitter.com/jenlooper) | +| 11 | 비율 시각화 | [데이터 시각화](3-Data-Visualization/README.md) | 이산 및 그룹화된 백분율 시각화. | [강의](3-Data-Visualization/11-visualization-proportions/README.md) | [Jen](https://twitter.com/jenlooper) | +| 12 | 관계 시각화 | [데이터 시각화](3-Data-Visualization/README.md) | 데이터 집합과 변수 간 연결 및 상관관계 시각화. | [강의](3-Data-Visualization/12-visualization-relationships/README.md) | [Jen](https://twitter.com/jenlooper) | +| 13 | 유의미한 시각화 | [데이터 시각화](3-Data-Visualization/README.md) | 효과적인 문제 해결과 통찰을 위한 가치 있는 시각화 기법과 안내. | [강의](3-Data-Visualization/13-meaningful-visualizations/README.md) | [Jen](https://twitter.com/jenlooper) | +| 14 | 데이터 과학 수명주기 소개 | [수명주기](4-Data-Science-Lifecycle/README.md) | 데이터 수집과 추출이라는 데이터 과학 수명주기 첫 단계 소개. | [강의](4-Data-Science-Lifecycle/14-Introduction/README.md) | [Jasmine](https://twitter.com/paladique) | +| 15 | 분석 | [수명주기](4-Data-Science-Lifecycle/README.md) | 데이터 과학 수명주기에서 데이터를 분석하는 기법에 집중. | [강의](4-Data-Science-Lifecycle/15-analyzing/README.md) | [Jasmine](https://twitter.com/paladique) | | | +| 16 | 커뮤니케이션 | [수명주기](4-Data-Science-Lifecycle/README.md) | 데이터 과학 수명주기에서 의사결정에 도움이 되도록 인사이트를 발표하는 단계. | [강의](4-Data-Science-Lifecycle/16-communication/README.md) | [Jalen](https://twitter.com/JalenMcG) | | | +| 17 | 클라우드에서의 데이터 과학 | [클라우드 데이터](5-Data-Science-In-Cloud/README.md) | 클라우드의 데이터 과학과 그 이점 소개. | [강의](5-Data-Science-In-Cloud/17-Introduction/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) | +| 18 | 클라우드에서의 데이터 과학 | [클라우드 데이터](5-Data-Science-In-Cloud/README.md) | Low Code 도구를 사용한 모델 학습. |[강의](5-Data-Science-In-Cloud/18-Low-Code/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) | +| 19 | 클라우드에서의 데이터 과학 | [클라우드 데이터](5-Data-Science-In-Cloud/README.md) | Azure Machine Learning Studio를 사용한 모델 배포. | [강의](5-Data-Science-In-Cloud/19-Azure/README.md)| [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) | +| 20 | 현실 세계의 데이터 과학 | [현실 세계](6-Data-Science-In-Wild/README.md) | 실제 세계에서 데이터 과학이 주도하는 프로젝트. | [강의](6-Data-Science-In-Wild/20-Real-World-Examples/README.md) | [Nitya](https://twitter.com/nitya) | ## GitHub Codespaces -이 샘플을 Codespace에서 열려면 다음 단계를 따르세요: -1. 코드 드롭다운 메뉴를 클릭하고 "Open with Codespaces" 옵션을 선택합니다. -2. 창 아래쪽에서 "+ New codespace"를 선택합니다. -자세한 내용은 [GitHub 문서](https://docs.github.com/en/codespaces/developing-in-codespaces/creating-a-codespace-for-a-repository#creating-a-codespace)를 참고하세요. +다음 단계를 따라 이 샘플을 Codespace에서 열어보세요: +1. Code 드롭다운 메뉴를 클릭하고 Open with Codespaces 옵션을 선택합니다. +2. 창 하단에서 + New codespace를 선택합니다. +자세한 내용은 [GitHub 문서](https://docs.github.com/en/codespaces/developing-in-codespaces/creating-a-codespace-for-a-repository#creating-a-codespace)를 참조하세요. ## VSCode 원격 - 컨테이너 -로컬 머신과 VSCode의 원격 - 컨테이너 확장을 사용하여 이 저장소를 컨테이너에서 여는 방법: +로컬 머신과 VSCode를 사용하여 이 저장소를 컨테이너에서 열려면 VS Code Remote - Containers 확장 기능을 따라 하세요: -1. 처음 개발 컨테이너를 사용하는 경우 [시작하기 문서](https://code.visualstudio.com/docs/devcontainers/containers#_getting-started)에서 시스템 요구 사항(예: Docker 설치)을 확인하세요. +1. 처음 개발 컨테이너를 사용한다면, 시스템이 사전 요구 사항(예: Docker 설치)을 충족하는지 [시작하기 문서](https://code.visualstudio.com/docs/devcontainers/containers#_getting-started)에서 확인하세요. -이 저장소를 사용하려면, 격리된 Docker 볼륨에 저장소를 열 수 있습니다: +이 저장소를 사용하려면, 격리된 Docker 볼륨 내에서 저장소를 열 수 있습니다: -**참고**: 내부적으로 Remote-Containers: **Clone Repository in Container Volume...** 명령을 사용하여 소스 코드를 로컬 파일 시스템이 아닌 Docker 볼륨에 복제합니다. [볼륨](https://docs.docker.com/storage/volumes/)은 컨테이너 데이터를 지속시키는 권장 메커니즘입니다. +**참고**: 내부적으로 Remote-Containers: **Clone Repository in Container Volume...** 명령을 사용하여 소스 코드를 로컬 파일 시스템 대신 Docker 볼륨에 복제합니다. [볼륨](https://docs.docker.com/storage/volumes/)은 컨테이너 데이터 영속화를 위한 권장 방법입니다. -또는 저장소를 로컬에 클론하거나 다운로드한 뒤 열 수도 있습니다: +또는 로컬에 복제하거나 다운로드한 저장소를 열 수 있습니다: -- 이 저장소를 로컬 파일 시스템에 클론하세요. -- F1 키를 누르고 **Remote-Containers: Open Folder in Container...** 명령을 선택하세요. -- 클론한 폴더를 선택하고, 컨테이너가 시작될 때까지 기다린 후 실행해보세요. +- 이 저장소를 로컬 파일 시스템에 복제하세요. +- F1을 누르고 **Remote-Containers: Open Folder in Container...** 명령을 선택하세요. +- 복제한 폴더를 선택하고 컨테이너 시작을 기다린 후 사용해 보세요. ## 오프라인 접근 -[Docsify](https://docsify.js.org/#/)를 사용해 이 문서를 오프라인에서 실행할 수 있습니다. 이 저장소를 포크한 후, 로컬 머신에 [Docsify](https://docsify.js.org/#/quickstart)를 설치하세요. 그리고 저장소 루트 폴더에서 `docsify serve`를 실행하면 웹사이트가 localhost의 3000번 포트에서 서빙됩니다: `localhost:3000`. +이 문서를 오프라인에서 보려면 [Docsify](https://docsify.js.org/#/)를 사용하세요. 이 저장소를 포크하고, 로컬 머신에 [Docsify](https://docsify.js.org/#/quickstart)를 설치한 후 저장소 루트 폴더에서 `docsify serve`를 실행하세요. 로컬호스트의 3000 포트(`localhost:3000`)에서 웹사이트가 서비스됩니다. -> 참고로, 노트북은 Docsify를 통해 렌더링되지 않으므로 노트북을 실행해야 할 때는 별도로 VS Code에서 Python 커널로 실행하세요. +> 참고로, 노트북은 Docsify를 통해 렌더링되지 않으므로 노트북을 실행해야 할 때는 Python 커널이 실행 중인 VS Code에서 별도로 실행하세요. -## 다른 교육 과정들 +## 기타 커리큘럼 -저희 팀은 다른 교육 과정도 제작합니다! 확인해보세요: +저희 팀은 다른 커리큘럼도 제작합니다! 확인해보세요: ### LangChain -[![LangChain4j for Beginners](https://img.shields.io/badge/LangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchain4j-for-beginners) -[![LangChain.js for Beginners](https://img.shields.io/badge/LangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin) +[![초보자를 위한 LangChain4j](https://img.shields.io/badge/LangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchain4j-for-beginners) +[![초보자를 위한 LangChain.js](https://img.shields.io/badge/LangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin) --- -### Azure / Edge / MCP / Agents -[![AZD for Beginners](https://img.shields.io/badge/AZD%20for%20Beginners-0078D4?style=for-the-badge&labelColor=E5E7EB&color=0078D4)](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst) -[![Edge AI for Beginners](https://img.shields.io/badge/Edge%20AI%20for%20Beginners-00B8E4?style=for-the-badge&labelColor=E5E7EB&color=00B8E4)](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst) -[![MCP for Beginners](https://img.shields.io/badge/MCP%20for%20Beginners-009688?style=for-the-badge&labelColor=E5E7EB&color=009688)](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst) -[![AI Agents for Beginners](https://img.shields.io/badge/AI%20Agents%20for%20Beginners-00C49A?style=for-the-badge&labelColor=E5E7EB&color=00C49A)](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst) +### Azure / Edge / MCP / 에이전트 +[![초보자를 위한 AZD](https://img.shields.io/badge/AZD%20for%20Beginners-0078D4?style=for-the-badge&labelColor=E5E7EB&color=0078D4)](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst) +[![초보자를 위한 Edge AI](https://img.shields.io/badge/Edge%20AI%20for%20Beginners-00B8E4?style=for-the-badge&labelColor=E5E7EB&color=00B8E4)](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst) +[![초보자를 위한 MCP](https://img.shields.io/badge/MCP%20for%20Beginners-009688?style=for-the-badge&labelColor=E5E7EB&color=009688)](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst) +[![초보자를 위한 AI 에이전트](https://img.shields.io/badge/AI%20Agents%20for%20Beginners-00C49A?style=for-the-badge&labelColor=E5E7EB&color=00C49A)](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst) --- ### 생성형 AI 시리즈 -[![Generative AI for Beginners](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) -[![Generative AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) -[![Generative AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) -[![Generative AI (JavaScript)](https://img.shields.io/badge/Generative%20AI%20(JavaScript)-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst) +[![초보자를 위한 생성형 AI](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) +[![생성형 AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) +[![생성형 AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) +[![생성형 AI (JavaScript)](https://img.shields.io/badge/Generative%20AI%20(JavaScript)-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst) --- -### 핵심 학습 -[![ML for Beginners](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) -[![Data Science for Beginners](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) -[![AI for Beginners](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) -[![Cybersecurity for Beginners](https://img.shields.io/badge/Cybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) -[![Web Dev for Beginners](https://img.shields.io/badge/Web%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) -[![IoT for Beginners](https://img.shields.io/badge/IoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) -[![XR Development for Beginners](https://img.shields.io/badge/XR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) +### 기본 학습 +[![초보자를 위한 ML](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) +[![초보자를 위한 데이터 과학](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) +[![초보자를 위한 AI](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) +[![초보자를 위한 사이버보안](https://img.shields.io/badge/Cybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) +[![초보자를 위한 웹 개발](https://img.shields.io/badge/Web%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) +[![초보자를 위한 IoT](https://img.shields.io/badge/IoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) +[![초보자를 위한 XR 개발](https://img.shields.io/badge/XR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) --- ### 코파일럿 시리즈 -[![Copilot for AI Paired Programming](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) -[![Copilot for C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) -[![Copilot Adventure](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) +[![AI 페어 프로그래밍을 위한 코파일럿](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) +[![C#/.NET용 코파일럿](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) +[![코파일럿 어드벤처](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) ## 도움 받기 -**문제가 발생했나요?** 일반적인 문제 해결 방법은 [문제 해결 가이드](TROUBLESHOOTING.md)에서 확인하세요. +**문제가 있나요?** 일반적인 문제 해결 방법은 [문제 해결 가이드](TROUBLESHOOTING.md)에서 확인하세요. -AI 앱 개발 중에 막히거나 궁금한 점이 있으면 MCP에 대해 배우는 동료 학습자와 경험 많은 개발자들이 모인 토론에 참여하세요. 질문을 환영하고 지식을 자유롭게 공유하는 지원 커뮤니티입니다. +AI 앱 개발 중에 막히거나 질문이 있으면 MCP 학습자 및 숙련된 개발자들과 함께 토론에 참여하세요. 질문이 환영받고 지식이 자유롭게 공유되는 지원 커뮤니티입니다. [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -제품 피드백이나 빌드 중 오류가 있으면 다음을 방문하세요: +제품 피드백이나 빌드 중 발생하는 오류는 다음에서 알려주세요: -[![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) +[![Microsoft Foundry 개발자 포럼](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) --- **면책 조항**: -이 문서는 AI 번역 서비스 [Co-op Translator](https://github.com/Azure/co-op-translator)를 사용하여 번역되었습니다. 정확성을 위해 노력하였으나, 자동 번역에는 오류나 부정확한 부분이 있을 수 있음을 유의하시기 바랍니다. 원문 문서가 권위 있는 공식 자료로 간주되어야 합니다. 중요한 정보의 경우, 전문 인력의 번역을 권장합니다. 본 번역의 사용으로 발생하는 어떠한 오해나 잘못된 해석에 대해서도 책임을 지지 않습니다. +이 문서는 AI 번역 서비스 [Co-op Translator](https://github.com/Azure/co-op-translator)를 사용하여 번역되었습니다. 정확성을 위해 노력했으나, 자동 번역에는 오류나 부정확성이 포함될 수 있음을 유의하시기 바랍니다. 원본 문서가 권위 있는 출처로 간주되어야 합니다. 중요한 정보에 대해서는 전문 번역가의 번역을 권장합니다. 본 번역 사용으로 인해 발생하는 오해나 잘못된 해석에 대해 당사는 책임을 지지 않습니다. \ No newline at end of file diff --git a/translations/ko/SECURITY.md b/translations/ko/SECURITY.md index 9e7cbef9..55605ae6 100644 --- a/translations/ko/SECURITY.md +++ b/translations/ko/SECURITY.md @@ -1,12 +1,3 @@ - ## 보안 Microsoft는 소프트웨어 제품과 서비스의 보안을 매우 중요하게 생각하며, 여기에는 [Microsoft](https://github.com/Microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet](https://github.com/aspnet), [Xamarin](https://github.com/xamarin), 그리고 [Microsoft의 GitHub 조직들](https://opensource.microsoft.com/)을 통해 관리되는 모든 소스 코드 저장소가 포함됩니다. diff --git a/translations/ko/SUPPORT.md b/translations/ko/SUPPORT.md index 317e3953..fbcff5af 100644 --- a/translations/ko/SUPPORT.md +++ b/translations/ko/SUPPORT.md @@ -1,12 +1,3 @@ - # 지원 ## 문제 신고 및 도움 받는 방법 diff --git a/translations/ko/TROUBLESHOOTING.md b/translations/ko/TROUBLESHOOTING.md index 295afa4b..41a1251a 100644 --- a/translations/ko/TROUBLESHOOTING.md +++ b/translations/ko/TROUBLESHOOTING.md @@ -1,12 +1,3 @@ - # 문제 해결 가이드 이 가이드는 Data Science for Beginners 커리큘럼을 사용하는 동안 발생할 수 있는 일반적인 문제에 대한 해결책을 제공합니다. diff --git a/translations/ko/USAGE.md b/translations/ko/USAGE.md index 14b6cab6..8a9bb7c0 100644 --- a/translations/ko/USAGE.md +++ b/translations/ko/USAGE.md @@ -1,12 +1,3 @@ - # 사용 가이드 이 가이드는 초보자를 위한 데이터 과학 커리큘럼을 사용하는 예제와 일반적인 워크플로를 제공합니다. diff --git a/translations/ko/docs/_sidebar.md b/translations/ko/docs/_sidebar.md index 4932e884..e2a5b763 100644 --- a/translations/ko/docs/_sidebar.md +++ b/translations/ko/docs/_sidebar.md @@ -1,12 +1,3 @@ - - 소개 - [데이터 과학 정의하기](../1-Introduction/01-defining-data-science/README.md) - [데이터 과학 윤리](../1-Introduction/02-ethics/README.md) diff --git a/translations/ko/examples/README.md b/translations/ko/examples/README.md index 160a49a0..ff5d14eb 100644 --- a/translations/ko/examples/README.md +++ b/translations/ko/examples/README.md @@ -1,12 +1,3 @@ - # 초보자를 위한 데이터 과학 예제 예제 디렉토리에 오신 것을 환영합니다! 이 간단하고 잘 주석 처리된 예제 모음은 데이터 과학을 처음 접하는 분들도 쉽게 시작할 수 있도록 설계되었습니다. diff --git a/translations/ko/for-teachers.md b/translations/ko/for-teachers.md index 2a7d51b1..7a33dc18 100644 --- a/translations/ko/for-teachers.md +++ b/translations/ko/for-teachers.md @@ -1,12 +1,3 @@ - ## 교육자를 위한 안내 이 커리큘럼을 교실에서 사용하고 싶으신가요? 자유롭게 활용하세요! diff --git a/translations/ko/quiz-app/README.md b/translations/ko/quiz-app/README.md index 938753b6..b82375dd 100644 --- a/translations/ko/quiz-app/README.md +++ b/translations/ko/quiz-app/README.md @@ -1,12 +1,3 @@ - # 퀴즈 이 퀴즈는 데이터 과학 커리큘럼의 강의 전후 퀴즈로, https://aka.ms/datascience-beginners에서 확인할 수 있습니다. diff --git a/translations/ko/sketchnotes/README.md b/translations/ko/sketchnotes/README.md index 801db96f..ea7f4c87 100644 --- a/translations/ko/sketchnotes/README.md +++ b/translations/ko/sketchnotes/README.md @@ -1,12 +1,3 @@ - 스케치노트를 모두 여기에서 찾아보세요! ## 크레딧