Your index to the open-source companion repositories for DeepLearning.AI courses. Each course's notebooks, labs, starter projects, and reading materials live in their own GitHub repo — this page links you to all of them.
DeepLearning.AI is a global educational technology company founded by Andrew Ng with a mission to grow and connect the AI community. Through hands-on courses, specializations, and short courses, DeepLearning.AI helps millions of learners worldwide gain practical skills in machine learning, deep learning, generative AI, AI agents, and applied AI engineering.
What you'll find on the platform:
- Short Courses — focused 1–2 hour sessions on a single technique or tool, built with industry partners like Anthropic, NVIDIA, Google, and LandingAI.
- Specializations — multi-course tracks covering foundational topics like the Deep Learning Specialization and Generative AI for Everyone.
- Professional Certificates — career-oriented programs (e.g., the upcoming PyTorch Professional Certificate).
- The Batch — DeepLearning.AI's weekly newsletter covering AI news and analysis.
This page is a directory of the companion repositories for the courses listed below — each course's code and materials live in its own GitHub repo, linked from the catalog. Course videos and instruction live on deeplearning.ai.
| Folder | What's inside |
|---|---|
Learner Tooling/ |
Helper tools learners can use across courses (e.g., database viewers) |
Course code lives in separate GitHub repositories — one per course. Browse the Course Catalog below and use each course's GitHub link to open its companion repo, then follow that repo's README.md for setup instructions specific to that course.
This is not an exhaustive list of courses — browse our full catalog at deeplearning.ai.
Click any course title to visit the course page on DeepLearning.AI. Use the GitHub link to jump to the companion code in this repo.
Not sure what course to start with? Chat with (virtual) Andrew Ng to learn where your skills are at and where you should go next → Skill Builder
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Spec-Driven Development with Agentic Coding Assistants Learn the workflow for building software with AI coding agents using formal specifications. GitHub |
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Gemini CLI: Code and Create with an Open-Source Agent Build and customize an AI coding agent with Google's open-source Gemini CLI. GitHub |
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Governing AI Agents Hands-on labs for deploying AI agents responsibly with governance, evaluation, and oversight. GitHub |
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Document AI: From OCR to Agentic Doc Extraction Modern document processing with LandingAI — from OCR to agentic extraction pipelines on AWS. GitHub |
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Fast Prototyping of Gen AI Apps with Streamlit Build interactive generative AI apps fast using Streamlit on Snowflake. GitHub |
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Jupyter AI: AI Coding in Notebooks AI-assisted coding inside JupyterLab using the Jupyter AI extension. GitHub |
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Claude Code: A Highly Agentic Coding Assistant Build, debug, and ship software with Claude Code, Anthropic's agentic coding CLI. GitHub |
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Agent Skills with Anthropic Build reusable, composable agent skills using Anthropic's skill framework. GitHub |
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Build with Andrew Beginner-friendly, no-code course — learn to build AI-powered web apps using structured prompts. No coding experience required. GitHub |
Browse the Course Catalog above and click the GitHub link for the course you want. Each course has its own companion repository.
git clone https://github.com/https-deeplearning-ai/<course-repo>.git
cd <course-repo>Each course has its own setup instructions, dependencies, and environment variables. Most use Python (Jupyter notebooks) or Node.js (TypeScript projects). Common steps:
# Python courses:
pip install -r requirements.txt
jupyter lab
# Node/TypeScript courses:
npm install
npm run devIf a course requires API keys, copy .env.example to .env and fill in your credentials.
These repos hold the companion code — the videos and structured instruction live on DeepLearning.AI. Find your course there to follow along.
DeepLearningRepo/
├── README.md ← you are here
├── Learner Tooling/ ← reusable tools across courses
│ └── database-viewer/
└── assets/ ← images and shared assets for this README
Course code is no longer stored in this repo — each course lives in its own GitHub repository, linked from the Course Catalog above.
Do I need to pay to take these courses? All course videos are free. The Pro membership ($25/mo billed annually) adds hands-on labs, Professional Certificates, portfolio projects, exclusive courses from Andrew Ng, and personalized feedback.
Do I need prior experience? It depends on the course. Beginner-friendly options like Build with Andrew require no coding background. Most short courses assume basic Python or familiarity with LLMs.
Can I use this code in my own projects? Yes — code is provided for educational use. Check the LICENSE file in each course's repo for specifics.
How do I report bugs or suggest improvements? Open an issue in the relevant course's GitHub repository, or use the contact form on DeepLearning.AI.
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