yogeshhk/TeachingDataScience

What it solves

Learning to teach or study data science often requires assembling scattered materials and code. This project provides ready-to-use, freely licensed slide decks and code so anyone can teach or learn foundational and advanced topics without starting from scratch.

How it works

Content is organized into three levels: Courses (full curricula, ~40 hours), Workshops (one topic in depth, 8–16 hours), and Seminars (focused 1–2 hour sessions). Every session compiles from LaTeX sources into both presentation slides and two-column printable cheat-sheet notes. The repository also contains a Code/ directory with runnable Python notebooks and scripts for many topics, each with environment files and pytest tests. Slides are built as PDFs from .tex files in LaTeX/.

Who it’s for

Educators, self-learners, and practitioners who want to teach or quickly pick up data science concepts and practical examples. It’s also useful for anyone building course materials or examples from well-cited public sources.

Highlights

• Free and open-source (MIT licensed), built from well-cited public material.
• Three tiered formats: courses, workshops, and seminars — from 1 hour to full courses.
• Both slides and printable cheat-sheet notes generated from the same LaTeX source.
• Runnable Python code projects covering LangChain, LangGraph, RAG pipelines, fine-tuning, classical ML, NLP, GNNs, and more.
• Each code project includes conda environment files and pytest test suites.
• Full course catalog in COURSES.md with links to every driver file.