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Open Learning Stack 🚀

A single repo to learn and master Programming Languages + AI/ML concepts — with examples, hands-on exercises, and structured order.

Topics Languages License Status

What is this?

This is a structured, self-paced learning repository covering Python, JavaScript, TypeScript, Go, and Rust — plus a complete AI/ML track from math foundations to LLMs and MLOps. Every topic follows a consistent 4-file pattern: read the concept, run the example, solve the exercises, check the solutions. No ambiguity, no guessing where to start.

How to use this repo

# 1. Clone the repo
git clone https://github.com/iam-prabha/open-learning-stack.git
cd open-learning-stack

# 2. Pick a language folder (e.g. python/)
cd python/01-fundamentals/01-variables/

# 3. Open a topic folder — read, run, practice
cat README.md              # Read the concept
python example.py          # Run the demo
python exercise.py         # Try the exercises (fill in TODOs)
python solution.py         # Check the answers

Run on your device (no setup needed)

You don't need to install any compiler. Copy any code file and paste it into a free online editor:

Track Where to run Link
Python CodeChef IDE codechef.com/ide
Python (AI/ML) Google Colab colab.research.google.com
JavaScript JSFiddle jsfiddle.net
TypeScript TypeScript Playground typescriptlang.org/play
Go Go Playground go.dev/play
Rust Rust Playground play.rust-lang.org

All languages in one place: Replit supports every language in this repo (free account required).

Quick start

  1. Open any example.py, exercise.py, or solution.py in this repo
  2. Copy the code
  3. Paste into the matching platform above
  4. Hit Run

AI/ML notebooks: Upload notebook.ipynb directly to Google Colab, or paste notebook.py into a Colab code cell.

Repository structure

open-learning-stack/
├── _templates/          ← boilerplate for new topics
├── python/              ← 🐍 Python (fundamentals → advanced)
├── javascript/          ← 🟨 JavaScript (fundamentals → advanced)
├── typescript/          ← 🔷 TypeScript (fundamentals → advanced)
├── go/                  ← 🐹 Go (fundamentals → advanced)
├── rust/                ← 🦀 Rust (fundamentals → advanced)
├── ai-ml/               ← 🤖 AI/ML (math → ML → DL → LLMs → MLOps)
├── ROADMAP.md           ← Visual learning roadmap
├── GLOSSARY.md          ← Shared terminology
└── README.md            ← You are here

Languages

Language Status Topics Start here
Python 🟢 Active 24 python/01-fundamentals/01-variables
JavaScript 🟢 Active 23 javascript/01-fundamentals/01-variables
TypeScript 🟢 Active 23 typescript/01-fundamentals/01-types-and-annotations
Go 🟡 Planned 23 go/01-fundamentals/01-variables
Rust 🟡 Planned 23 rust/01-fundamentals/01-variables

AI/ML Roadmap

Phase Folder Focus Topics Status
0 ai-ml/01-math-foundations/ Linear algebra, calculus, probability 5 🟢 Active
1 ai-ml/02-ml-core/ Classical ML algorithms 8 🟢 Active
2 ai-ml/03-deep-learning/ Neural networks, CNNs, RNNs 6 🟢 Active
3 ai-ml/04-llms/ Transformers, fine-tuning, RAG 6 🟡 Planned
4 ai-ml/05-mlops/ Deployment, monitoring, CI/CD 5 🟡 Planned

The 4-file pattern

Every topic folder contains the same 4 files:

File Purpose
README.md Concept explanation with analogy, use cases, common mistakes
example.[ext] One clean, runnable demo — annotated with WHY comments
exercise.[ext] 6 TODOs + 1 challenge — with assert-based self-checking
solution.[ext] Complete answers with WHY comments and alternative approaches

This pattern ensures every topic is self-contained — you never need to look outside the folder.

Contributing

Everyone is welcome! To add a new topic:

  1. Copy _templates/ to the correct location (e.g. python/01-fundamentals/11-new-topic/)
  2. Fill in all 4 files following the patterns in existing topics
  3. Ensure example.[ext] and solution.[ext] run with zero errors
  4. Ensure exercise.[ext] has asserts that fail until TODOs are filled in
  5. Open a PR with a short description

See ROADMAP.md for topics that need contributors.

License

This project is licensed under the MIT License — see the LICENSE file for details.


Made with ❤️ by @iam-prabha — Happy learning! 🎓✨

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This repo provide resources for data science & AI/ ML and keep actively update content for everyone to learn

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