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fucking-awesome-datascience

github.com/correia-jpv/fucking-awesome-datascience ↗

📝 An awesome Data Science repository to learn and apply for real world problems. With repository stars⭐ and forks🍴

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GitHub Stars
915
Curated Resources
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1 hour ago
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What is Data Science?AgentsTraining ResourcesThe Data Science ToolboxLiterature and MediaSocializeFunOther Awesome Lists

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What's inside

Fun

  • 🌎Infographics

    🌎 Choosing the Right Estimator

  • 🌎Infographics

    The Data Science Industry: Who Does What

  • 🌎Infographics

    Mindmap on required skills 🌎 img )

  • 🌎Infographics

    by 🌎 @kzawadz via 🌎 twitter

  • 🌎Infographics

    Swami Chandrasekaran made a Curriculum via Metro map .

  • 🌎Infographics

    A simple and friendly way of teaching your non-data scientist/non-statistician colleagues 🌎 how to avoid mistakes with data . From Geckoboard's 🌎 Data Literacy Lessons .

Other Awesome Lists

The Data Science Toolbox

  • 10463⭐AutoGluonMiscellaneous Tools

    AutoML to easily produce accurate predictions for image, text, tabular, time-series, and multi-modal data

  • 10885⭐KedroMiscellaneous Tools

    Open-source Python framework for creating reproducible, maintainable data science code

  • 11114⭐Weights & BiasesMiscellaneous Tools

    Experiment tracking, dataset versioning, and model management

  • 11502⭐cleanlabMiscellaneous Tools

    Python library for data-centric AI and automatically detecting various issues in ML datasets

  • 12141⭐LIMEMiscellaneous Tools

    Explaining the predictions of any machine learning classifier

  • 12963⭐dbtMiscellaneous Tools

    Data build tool

What is Data Science?

  • 35576⭐Data Science For Beginners

    Microsoft are pleased to offer a 10-week, 20-lesson curriculum all about Data Science.

  • 🌎 a very short history of #datascience

    The story of how data scientists became sexy is mostly the story of the coupling of the mature discipline of statistics with a very young one--computer science. The term “Data Science” has emerged only recently to specifically designate a new profession that is expected to make sense of the vast stores of big data. But making sense of data has a long history and has been discussed by scientists, statisticians, librarians, computer scientists and others for years. The following timeline traces the evolution of the term “Data Science” and its use, attempts to define it, and related terms.

Literature and Media

Agents

  • ADK-RustFrameworks

    Production-ready AI agent development kit for Rust with model-agnostic design (Gemini, OpenAI, Anthropic), multiple agent types (LLM, Graph, Workflow), MCP support, and built-in telemetry.

  • ai-evaluationTools

    Open-source LLM and agent evaluation framework with 50+ metrics, LLM-as-Judge augmentation, and guardrail scanners (jailbreak, PII, prompt-injection). Useful for scoring RAG outputs, agent trajectories, and function-calling behavior in data-science workflows.

  • Arch ToolsTools

    61 production-ready AI API tools for data science workflows: code analysis, web scraping, NLP, image generation, crypto data, and search. REST API and MCP protocol support.

Socialize

Showing a sample of 915 resources. View the full list on GitHub →