# microsoft/Data-Science-For-Beginners

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## Links

- GitHub: https://github.com/microsoft/Data-Science-For-Beginners
- awesome-repositories: https://awesome-repositories.com/repository/microsoft-data-science-for-beginners.md

## Topics

`data-analysis` `data-science` `data-visualization` `microsoft-for-beginners` `pandas` `python`

## Description

This project is a comprehensive educational curriculum designed to teach the fundamental concepts, workflows, and tools of data science. It provides a structured learning path that covers the end-to-end data science lifecycle, including data acquisition, maintenance, processing, and pattern discovery, while grounding theoretical knowledge in practical, real-world applications.

The curriculum distinguishes itself through a data-driven pedagogical design that utilizes interactive, notebook-based lessons. By combining narrative text with live code blocks, the platform allows learners to experiment with data analysis and visualization techniques in real time. The content is organized into a modular structure that sequences topics by progressive complexity, ensuring that foundational skills are established before moving into more advanced analytical techniques.

The material encompasses a broad capability surface, including tutorials on data visualization, relational database querying, and the integration of cloud computing into data science workflows. These resources rely on an established ecosystem of open-source libraries to ensure that the skills acquired are applicable to professional environments.

The repository is hosted as a centralized collection of instructional modules and guided exercises. It includes self-contained code samples and assignments that require a standard Python environment to execute.

## Tags

### Education & Learning Resources

- [Data Science Curricula](https://awesome-repositories.com/f/education-learning-resources/data-science-curricula.md) — Provides introductory data science programming examples and guided learning exercises. ([source](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/examples/README.md))
- [Data Visualization Tutorials](https://awesome-repositories.com/f/education-learning-resources/data-visualization-tutorials.md) — Offers practical tutorials on using plotting libraries for data visualization. ([source](https://github.com/microsoft/Data-Science-For-Beginners#readme))
- [Interactive Notebooks](https://awesome-repositories.com/f/education-learning-resources/interactive-notebooks.md) — Delivers educational content through interactive, executable notebooks that allow for immediate code experimentation.
- [Cloud Computing Curricula](https://awesome-repositories.com/f/education-learning-resources/cloud-computing-curricula.md) — Provides educational resources on cloud computing benefits and service models. ([source](https://github.com/microsoft/Data-Science-For-Beginners#readme))
- [Data Querying Tutorials](https://awesome-repositories.com/f/education-learning-resources/data-querying-tutorials.md) — Provides instructional guides on relational database querying techniques. ([source](https://github.com/microsoft/Data-Science-For-Beginners#readme))
- [Database Fundamentals](https://awesome-repositories.com/f/education-learning-resources/database-fundamentals.md) — Explains the core concepts of relational tables and data organization. ([source](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/2-Working-With-Data/05-relational-databases/README.md))
- [Educational Repositories](https://awesome-repositories.com/f/education-learning-resources/educational-repositories.md) — Provides a structured collection of learning materials and hands-on exercises for foundational concepts.
- [Pedagogical Frameworks](https://awesome-repositories.com/f/education-learning-resources/pedagogical-frameworks.md) — Provides a structured pedagogical approach that organizes instructional content around practical data analysis.
- [Practical Assignments](https://awesome-repositories.com/f/education-learning-resources/practical-assignments.md) — Provides hands-on assignments for exploring datasets in a practical environment. ([source](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/2-Working-With-Data/05-relational-databases/README.md))
- [Sustainability Case Studies](https://awesome-repositories.com/f/education-learning-resources/sustainability-case-studies.md) — Includes case studies demonstrating data science applications across diverse fields. ([source](https://github.com/microsoft/Data-Science-For-Beginners#readme))

### Graphics & Multimedia

- [Data Visualization Libraries](https://awesome-repositories.com/f/graphics-multimedia/data-visualization-libraries.md) — Provides tools for creating interactive charts and graphical representations of data.
- [Data Visualization Tutorials](https://awesome-repositories.com/f/graphics-multimedia/data-visualization-tutorials.md) — Provides practical tutorials for building line plots using data science libraries. ([source](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/3-Data-Visualization/09-visualization-quantities/README.md))
- [Plotting Libraries](https://awesome-repositories.com/f/graphics-multimedia/plotting-libraries.md) — Introduces plotting libraries for creating sophisticated charts and data visualizations. ([source](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/3-Data-Visualization/09-visualization-quantities/README.md))
- [Bar Chart Implementations](https://awesome-repositories.com/f/graphics-multimedia/bar-chart-implementations.md) — Guides the creation of bar charts to visualize and compare categorical data groupings. ([source](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/3-Data-Visualization/09-visualization-quantities/README.md))
- [Comparative Visualization](https://awesome-repositories.com/f/graphics-multimedia/comparative-visualization.md) — Demonstrates how to compare grouped data by creating specific chart axes. ([source](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/3-Data-Visualization/09-visualization-quantities/README.md))

### Artificial Intelligence & ML

- [Cloud Machine Learning Examples](https://awesome-repositories.com/f/artificial-intelligence-ml/cloud-machine-learning-examples.md) — Provides tangible scenarios for applying machine learning techniques in cloud environments. ([source](https://github.com/microsoft/Data-Science-For-Beginners/blob/main/5-Data-Science-In-Cloud/17-Introduction/README.md))

### Development Tools & Productivity

- [Interactive Notebooks](https://awesome-repositories.com/f/development-tools-productivity/interactive-notebooks.md) — Ships executable documents that combine explanatory text with live code blocks for data processing.
