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>Photo by <ahref="https://unsplash.com/@dawson2406?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Stephen Dawson</a> on <ahref="https://unsplash.com/s/photos/data?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a>
In these lessons, you will discover how Data Science is defined and learn about ethical considerations that must be considered by a data scientist. You will also learn how data is defined and learn a bit about statistics and probability, the core academic domains of Data Science.
In these lessons, you will discover how Data Science is defined and learn about ethical considerations that must be considered by a data scientist. You will also learn how data is defined and learn a bit about statistics and probability, the core academic domains of Data Science.
### Topics
### Topics
1. [Defining Data Science](01-defining-data-science/README.md)
1. [Defining Data Science](01-defining-data-science/README.md)
>Photo by <ahref="https://unsplash.com/@dawson2406?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Stephen Dawson</a> on <ahref="https://unsplash.com/s/photos/data?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a>
इन पाठों में, आप जानेंगे कि डेटा विज्ञान को कैसे परिभाषित किया जाता है और उन नैतिक विचारों के बारे में जानेंगे जिन पर एक डेटा वैज्ञानिक को विचार करना चाहिए। आप यह भी जानेंगे कि डेटा को कैसे परिभाषित किया जाता है तथा आप डेटा की सांख्यिकी और संभाव्यता के बारे में भी थोरा सीखेगे जोकी एक डेटा विज्ञान के मुख्य शैक्षणिक डोमेन है ।
### विषय
1. [डेटा साइंस को परिभाषित करना](01-defining-data-science/README.md)
2. [डेटा साइंस एथिक्स](02-ethics/README.md)
3. [डेटा को परिभाषित करना](03-defining-data/README.md)
4. [सांख्यिकी और संभाव्यता का परिचय](04-stats-and-probability/README.md)
### क्रेडिट
ये पाठ [Nitya Narasimhan](https://twitter.com/nitya) और [Dmitry Soshnikov](https://twitter.com/shwars) द्वारा ❤️ के साथ लिखे गए थे।
> Photo by <ahref="https://unsplash.com/@dawson2406?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Stephen Dawson</a> on <ahref="https://unsplash.com/s/photos/data?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a>
Azure Cloud Advocates at Microsoft are pleased to offer a 10-week, 20-lesson curriculum all about Data Science. Each lesson includes pre-lesson and post-lesson quizzes, written instructions to complete the lesson, a solution, and an assignment. Our project-based pedagogy allows you to learn while building, a proven way for new skills to 'stick'.
Azure Cloud Advocates at Microsoft are pleased to offer a 10-week, 20-lesson curriculum all about Data Science. Each lesson includes pre-lesson and post-lesson quizzes, written instructions to complete the lesson, a solution, and an assignment. Our project-based pedagogy allows you to learn while building, a proven way for new skills to 'stick'.
| ](./sketchnotes/00-Title.png)|
| ](./sketchnotes/00-Title.png)|
|:---:|
|:---:|
@ -25,10 +35,9 @@ Azure Cloud Advocates at Microsoft are pleased to offer a 10-week, 20-lesson cur
We have chosen two pedagogical tenets while building this curriculum: ensuring that it is project-based and that it includes frequent quizzes. By the end of this series, students will have learned basic principles of data science, including ethical concepts, data preparation, different ways of working with data, data visualization, data analysis, real-world use cases of data science, and more.
We have chosen two pedagogical tenets while building this curriculum: ensuring that it is project-based and that it includes frequent quizzes. By the end of this series, students will have learned basic principles of data science, including ethical concepts, data preparation, different ways of working with data, data visualization, data analysis, real-world use cases of data science, and more.
In addition, a low-stakes quiz before a class sets the intention of the student towards learning a topic, while a second quiz after class ensures further retention. This curriculum was designed to be flexible and fun and can be taken in whole or in part. The projects start small and become increasingly complex by the end of the 12 week cycle.
In addition, a low-stakes quiz before a class sets the intention of the student towards learning a topic, while a second quiz after class ensures further retention. This curriculum was designed to be flexible and fun and can be taken in whole or in part. The projects start small and become increasingly complex by the end of the 10 week cycle.
> Find our [Code of Conduct](CODE_OF_CONDUCT.md), [Contributing](CONTRIBUTING.md), [Translation](TRANSLATIONS.md) guidelines. We welcome your constructive feedback!
> Find our [Code of Conduct](CODE_OF_CONDUCT.md), [Contributing](CONTRIBUTING.md), [Translation](TRANSLATIONS.md) guidelines. We welcome your constructive feedback!
>
## Each lesson includes:
## Each lesson includes:
@ -82,7 +91,7 @@ You can run this documentation offline by using [Docsify](https://docsify.js.org
> Note, notebooks will not be rendered via Docsify, so when you need to run a notebook, do that separately in VS Code running a Python kernel.
> Note, notebooks will not be rendered via Docsify, so when you need to run a notebook, do that separately in VS Code running a Python kernel.
## PDF
## PDF
A PDF of all of the lessons can be found [here](pdf/readme.pdf)
A PDF of all of the lessons can be found [here](https://microsoft.github.io/Data-Science-For-Beginners/pdf/readme.pdf)
Bernardo Romero
4 years ago