# academic/awesome-datascience

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## Links

- GitHub: https://github.com/academic/awesome-datascience
- awesome-repositories: https://awesome-repositories.com/repository/academic-awesome-datascience.md

## Topics

`analytics` `awesome-list` `data-mining` `data-science` `data-scientists` `data-visualization` `deep-learning` `hacktoberfest` `machine-learning` `science`

## Description

This project is a comprehensive, community-driven knowledge repository that serves as a centralized hub for data science resources. It provides a structured index of educational materials, software packages, and professional development tools designed to support both students and practitioners in navigating the data science landscape.

The repository distinguishes itself through a hierarchical taxonomy that organizes a vast collection of external links into a human-readable, markdown-based document. By relying on distributed contributions, the project maintains an up-to-date snapshot of the field, ranging from foundational machine learning frameworks and deep learning packages to academic journals and community-led platforms.

Beyond core software and learning materials, the index covers a broad spectrum of professional and technical support, including data science competitions, career development resources, and various media formats such as podcasts, newsletters, and video channels. This collection functions as a static, version-controlled reference point for anyone looking to acquire new skills or stay informed on industry advancements.

## Tags

### Artificial Intelligence & ML

- [Data Science Collections](https://awesome-repositories.com/f/artificial-intelligence-ml/data-science-collections.md) — Serves as a comprehensive hub for learning and applying data science techniques. ([source](https://github.com/academic/awesome-datascience#readme))
- [Data Science Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/data-science-frameworks.md) — Provides a curated list of frameworks for data science and analytics. ([source](https://github.com/academic/awesome-datascience#readme))
- [Deep Learning Libraries](https://awesome-repositories.com/f/artificial-intelligence-ml/deep-learning-libraries.md) — Lists essential packages and frameworks for deep learning development. ([source](https://github.com/academic/awesome-datascience#readme))
- [Machine Learning Libraries](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning-libraries.md) — Lists general-purpose machine learning packages for data science workflows. ([source](https://github.com/academic/awesome-datascience#readme))
- [Machine Learning Tooling](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning-tooling.md) — Helps identify and discover software libraries for machine learning.
- [Data Science Algorithms](https://awesome-repositories.com/f/artificial-intelligence-ml/data-science-algorithms.md) — Provides a curated list of algorithms used in data science and machine learning. ([source](https://github.com/academic/awesome-datascience#readme))

### Data & Databases

- [Data Science Hubs](https://awesome-repositories.com/f/data-databases/data-science-hubs.md) — Serves as a centralized hub for data science tools and research.
- [Data Science Toolkits](https://awesome-repositories.com/f/data-databases/data-science-toolkits.md) — Aggregates essential tools for data science workflows. ([source](https://github.com/academic/awesome-datascience#readme))
- [Public Datasets](https://awesome-repositories.com/f/data-databases/public-datasets.md) — Provides access to diverse datasets for training and analysis. ([source](https://github.com/academic/awesome-datascience#readme))

### Miscellaneous Curated Lists

- [Awesome Lists](https://awesome-repositories.com/f/miscellaneous-curated-lists/awesome-lists.md) — Acts as a meta-directory of other awesome lists for data science. ([source](https://github.com/academic/awesome-datascience#readme))
- [Knowledge Repositories](https://awesome-repositories.com/f/miscellaneous-curated-lists/knowledge-repositories.md) — Acts as a comprehensive curated collection of data science resources.
- [Markdown Curations](https://awesome-repositories.com/f/miscellaneous-curated-lists/markdown-curations.md) — Organizes vast collections of resources into a structured, human-readable document.
- [Community-Driven Collections](https://awesome-repositories.com/f/miscellaneous-curated-lists/community-driven-collections.md) — Facilitates collaborative maintenance and verification of resources by multiple contributors.

### Education & Learning Resources

- [Educational Indexes](https://awesome-repositories.com/f/education-learning-resources/educational-indexes.md) — Provides a structured directory of educational materials for data science.
- [Online Courses](https://awesome-repositories.com/f/education-learning-resources/online-courses.md) — Provides a curated list of free educational courses for data science. ([source](https://github.com/academic/awesome-datascience#readme))
- [MOOCs](https://awesome-repositories.com/f/education-learning-resources/moocs.md) — Lists massive open online courses for data science learning. ([source](https://github.com/academic/awesome-datascience#readme))
- [Skill Acquisition Guides](https://awesome-repositories.com/f/education-learning-resources/skill-acquisition-guides.md) — Provides curated educational materials for building data science skills.
- [Training Programs](https://awesome-repositories.com/f/education-learning-resources/training-programs.md) — Provides structured training resources for skill development. ([source](https://github.com/academic/awesome-datascience#readme))

### Development Tools & Productivity

- [Development Tools](https://awesome-repositories.com/f/development-tools-productivity/development-tools.md) — Provides a list of essential tools for data science development. ([source](https://github.com/academic/awesome-datascience#readme))