| 01 | Defining Data Science | [Introduction](1-Introduction/README.md) | Learn the basic concepts behind data science and how it’s related to artificial intelligence, machine learning, and big data. | [lesson](1-Introduction/01-defining-data-science/README.md) [video](https://youtu.be/beZ7Mb_oz9I) | [Dmitry](http://soshnikov.com) |
| 02 | Data Science Ethics | [Introduction](1-Introduction/README.md) | Data Ethics Concepts, Challenges & Frameworks. | [lesson](1-Introduction/02-ethics/README.md) | [Nitya](https://twitter.com/nitya) |
| 03 | Defining Data | [Introduction](1-Introduction/README.md) | How data is classified and its common sources. | [lesson](1-Introduction/03-defining-data/README.md) | [Jasmine](https://www.twitter.com/paladique) |
| 04 | Introduction to Statistics & Probability | [Introduction](1-Introduction/README.md) | The mathematical techniques of probability and statistics to understand data. | [lesson](1-Introduction/04-stats-and-probability/README.md) [video](https://youtu.be/Z5Zy85g4Yjw) | [Dmitry](http://soshnikov.com) |
| 05 | Working with Relational Data | [Working With Data](2-Working-With-Data/README.md) | Introduction to relational data and the basics of exploring and analyzing relational data with the Structured Query Language, also known as SQL (pronounced “see-quell”). | [lesson](2-Working-With-Data/05-relational-databases/README.md) | [Christopher](https://www.twitter.com/geektrainer) | | |
| 06 | Working with NoSQL Data | [Working With Data](2-Working-With-Data/README.md) | Introduction to non-relational data, its various types and the basics of exploring and analyzing document databases. | [lesson](2-Working-With-Data/06-non-relational/README.md) | [Jasmine](https://twitter.com/paladique)|
| 07 | Working with Python | [Working With Data](2-Working-With-Data/README.md) | Basics of using Python for data exploration with libraries such as Pandas. Foundational understanding of Python programming is recommended. | [lesson](2-Working-With-Data/07-python/README.md) [video](https://youtu.be/dZjWOGbsN4Y) | [Dmitry](http://soshnikov.com) |
| 08 | Data Preparation | [Working With Data](2-Working-With-Data/README.md) | Topics on data techniques for cleaning and transforming the data to handle challenges of missing, inaccurate, or incomplete data. | [lesson](2-Working-With-Data/08-data-preparation/README.md) | [Jasmine](https://www.twitter.com/paladique) |
| 09 | Visualizing Quantities | [Data Visualization](3-Data-Visualization/README.md) | Learn how to use Matplotlib to visualize bird data 🦆 | [lesson](3-Data-Visualization/09-visualization-quantities/README.md) | [Jen](https://twitter.com/jenlooper) |
| 10 | Visualizing Distributions of Data | [Data Visualization](3-Data-Visualization/README.md) | Visualizing observations and trends within an interval. | [lesson](3-Data-Visualization/10-visualization-distributions/README.md) | [Jen](https://twitter.com/jenlooper) |
| 12 | Visualizing Relationships | [Data Visualization](3-Data-Visualization/README.md) | Visualizing connections and correlations between sets of data and their variables. | [lesson](3-Data-Visualization/12-visualization-relationships/README.md) | [Jen](https://twitter.com/jenlooper) |
| 13 | Meaningful Visualizations | [Data Visualization](3-Data-Visualization/README.md) | Techniques and guidance for making your visualizations valuable for effective problem solving and insights. | [lesson](3-Data-Visualization/13-meaningful-visualizations/README.md) | [Jen](https://twitter.com/jenlooper) |
| 14 | Introduction to the Data Science lifecycle | [Lifecycle](4-Data-Science-Lifecycle/README.md) | Introduction to the data science lifecycle and its first step of acquiring and extracting data. | [lesson](4-Data-Science-Lifecycle/14-Introduction/README.md) | [Jasmine](https://twitter.com/paladique) |
| 15 | Analyzing | [Lifecycle](4-Data-Science-Lifecycle/README.md) | This phase of the data science lifecycle focuses on techniques to analyze data. | [lesson](4-Data-Science-Lifecycle/15-analyzing/README.md) | [Jasmine](https://twitter.com/paladique) | | |
| 16 | Communication | [Lifecycle](4-Data-Science-Lifecycle/README.md) | This phase of the data science lifecycle focuses on presenting the insights from the data in a way that makes it easier for decision makers to understand. | [lesson](4-Data-Science-Lifecycle/16-communication/README.md) | [Jalen](https://twitter.com/JalenMcG) | | |
| 17 | Data Science in the Cloud | [Cloud Data](5-Data-Science-In-Cloud/README.md) | This series of lessons introduces data science in the cloud and its benefits. | [lesson](5-Data-Science-In-Cloud/17-Introduction/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) |
| 18 | Data Science in the Cloud | [Cloud Data](5-Data-Science-In-Cloud/README.md) | Training models using Low Code tools. |[lesson](5-Data-Science-In-Cloud/18-Low-Code/README.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) |
| 19 | Data Science in the Cloud | [Cloud Data](5-Data-Science-In-Cloud/README.md) | Deploying models with Azure Machine Learning Studio. | [lesson](5-Data-Science-In-Cloud/19-Azure/README.md)| [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) |
| 20 | Data Science in the Wild | [In the Wild](6-Data-Science-In-Wild/README.md) | Data science driven projects in the real world. | [lesson](6-Data-Science-In-Wild/20-Real-World-Examples/README.md) | [Nitya](https://twitter.com/nitya) |
| 01 | Defining Data Science | [Introduction](1-Introduction/translations/README.ko.md) | Learn the basic concepts behind data science and how it’s related to artificial intelligence, machine learning, and big data. | [lesson](1-Introduction/01-defining-data-science/translations/README.ko.md) [video](https://youtu.be/beZ7Mb_oz9I) | [Dmitry](http://soshnikov.com) |
| 02 | Data Science Ethics | [Introduction](1-Introduction/translations/README.ko.md) | Data Ethics Concepts, Challenges & Frameworks. | [lesson](1-Introduction/02-ethics/translations/README.ko.md) | [Nitya](https://twitter.com/nitya) |
| 03 | Defining Data | [Introduction](1-Introduction/translations/README.ko.md) | How data is classified and its common sources. | [lesson](1-Introduction/03-defining-data/translations/README.ko.md) | [Jasmine](https://www.twitter.com/paladique) |
| 04 | Introduction to Statistics & Probability | [Introduction](1-Introduction/translations/README.ko.md) | The mathematical techniques of probability and statistics to understand data. | [lesson](1-Introduction/04-stats-and-probability/translations/README.ko.md) [video](https://youtu.be/Z5Zy85g4Yjw) | [Dmitry](http://soshnikov.com) |
| 05 | Working with Relational Data | [Working With Data](2-Working-With-Data/translations/README.ko.md) | Introduction to relational data and the basics of exploring and analyzing relational data with the Structured Query Language, also known as SQL (pronounced “see-quell”). | [lesson](2-Working-With-Data/05-relational-databases/translations/README.ko.md) | [Christopher](https://www.twitter.com/geektrainer) | | |
| 06 | Working with NoSQL Data | [Working With Data](2-Working-With-Data/translations/README.ko.md) | Introduction to non-relational data, its various types and the basics of exploring and analyzing document databases. | [lesson](2-Working-With-Data/06-non-relational/translations/README.ko.md) | [Jasmine](https://twitter.com/paladique)|
| 07 | Working with Python | [Working With Data](2-Working-With-Data/translations/README.ko.md) | Basics of using Python for data exploration with libraries such as Pandas. Foundational understanding of Python programming is recommended. | [lesson](2-Working-With-Data/07-python/translations/README.ko.md) [video](https://youtu.be/dZjWOGbsN4Y) | [Dmitry](http://soshnikov.com) |
| 08 | Data Preparation | [Working With Data](2-Working-With-Data/translations/README.ko.md) | Topics on data techniques for cleaning and transforming the data to handle challenges of missing, inaccurate, or incomplete data. | [lesson](2-Working-With-Data/08-data-preparation/translations/README.ko.md) | [Jasmine](https://www.twitter.com/paladique) |
| 09 | Visualizing Quantities | [Data Visualization](3-Data-Visualization/translations/README.ko.md) | Learn how to use Matplotlib to visualize bird data 🦆 | [lesson](3-Data-Visualization/09-visualization-quantities/translations/README.ko.md) | [Jen](https://twitter.com/jenlooper) |
| 10 | Visualizing Distributions of Data | [Data Visualization](3-Data-Visualization/translations/README.ko.md) | Visualizing observations and trends within an interval. | [lesson](3-Data-Visualization/10-visualization-distributions/translations/README.ko.md) | [Jen](https://twitter.com/jenlooper) |
| 12 | Visualizing Relationships | [Data Visualization](3-Data-Visualization/translations/README.ko.md) | Visualizing connections and correlations between sets of data and their variables. | [lesson](3-Data-Visualization/12-visualization-relationships/translations/README.ko.md) | [Jen](https://twitter.com/jenlooper) |
| 13 | Meaningful Visualizations | [Data Visualization](3-Data-Visualization/translations/README.ko.md) | Techniques and guidance for making your visualizations valuable for effective problem solving and insights. | [lesson](3-Data-Visualization/13-meaningful-visualizations/README.md) | [Jen](https://twitter.com/jenlooper) |
| 14 | Introduction to the Data Science lifecycle | [Lifecycle](4-Data-Science-Lifecycle/README.md) | Introduction to the data science lifecycle and its first step of acquiring and extracting data. | [lesson](4-Data-Science-Lifecycle/14-Introduction/translations/assignment.ko.md) | [Jasmine](https://twitter.com/paladique) |
| 15 | Analyzing | [Lifecycle](4-Data-Science-Lifecycle/README.md) | This phase of the data science lifecycle focuses on techniques to analyze data. | [lesson](4-Data-Science-Lifecycle/15-analyzing/translations/README.ko.md) | [Jasmine](https://twitter.com/paladique) | | |
| 16 | Communication | [Lifecycle](4-Data-Science-Lifecycle/README.md) | This phase of the data science lifecycle focuses on presenting the insights from the data in a way that makes it easier for decision makers to understand. | [lesson](4-Data-Science-Lifecycle/16-communication/translations/README.ko.md) | [Jalen](https://twitter.com/JalenMcG) | | |
| 17 | Data Science in the Cloud | [Cloud Data](5-Data-Science-In-Cloud/translations/README.ko.md) | This series of lessons introduces data science in the cloud and its benefits. | [lesson](5-Data-Science-In-Cloud/17-Introduction/translations/README.ko.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) |
| 18 | Data Science in the Cloud | [Cloud Data](5-Data-Science-In-Cloud/translations/README.ko.md) | Training models using Low Code tools. |[lesson](5-Data-Science-In-Cloud/18-Low-Code/translations/README.ko.md) | [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) |
| 19 | Data Science in the Cloud | [Cloud Data](5-Data-Science-In-Cloud/translations/README.ko.md) | Deploying models with Azure Machine Learning Studio. | [lesson](5-Data-Science-In-Cloud/19-Azure/translations/README.ko.md)| [Tiffany](https://twitter.com/TiffanySouterre) and [Maud](https://twitter.com/maudstweets) |
| 20 | Data Science in the Wild | [In the Wild](6-Data-Science-In-Wild/translations/README.ko.md) | Data science driven projects in the real world. | [lesson](6-Data-Science-In-Wild/20-Real-World-Examples/translations/README.ko.md) | [Nitya](https://twitter.com/nitya) |
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