From Zero to
AI Hero.

Anthropic's official learning platform — 13+ free courses covering Claude fundamentals, API, MCP, Claude Code, agents, AWS Bedrock & Google Vertex. Official certificates shareable on LinkedIn.

Core Claude features, practical workflows, and best practices for using Claude in real work. The essential first course for any Claude user.

Hands-on course for dropping Claude Code into your dev workflow. Ship faster, review smarter, and automate the boring parts of software engineering.

Essentials of the Claude SDK — authentication, messages, streaming, tool use, and prompt caching. Start building real applications.

Zero to building MCP servers and clients in Python — covering tools, prompts, and resources end to end. The emerging standard for AI integrations.

9-chapter Jupyter notebook course with hands-on exercises covering every major prompting technique for Claude. The canonical reference for Claude prompt engineering.

The master repository for all Anthropic educational courses as Jupyter notebooks — prompt engineering, real-world prompting, API fundamentals, tool use, and agents.

Production-ready code recipes for Claude — retrieval, tool use, multimodal inputs, agent patterns, and more. Copy, adapt, ship.

Build a strong mental model for how AI works, what it can and can't do, and how to think about it strategically. No technical background needed.

The world's most popular free AI intro course — 2M+ learners from 170+ countries. No math or coding required. Earns an official University of Helsinki certificate.

Google's practical AI skills course for professionals. Learn to use AI tools to dramatically boost your productivity at work — no coding needed.

The world's most widely taken non-technical AI course. Understand what AI can and can't do, how to spot opportunities, and how to work with AI teams. By Andrew Ng.

A practical, non-technical introduction to generative AI — what it is, how it works, limitations, and responsible use. The perfect first course on LLMs.

Google's short intro course on what Generative AI is, how it's used, and how it differs from traditional machine learning methods.

10+ Google-curated courses covering LLMs, prompt design, responsible AI, and building gen AI applications from scratch.

Microsoft's 24-lesson, 12-week open-source curriculum covering symbolic AI, neural networks, computer vision, NLP, and more — with Jupyter notebook exercises throughout.

IBM's widely-taken beginner course: what AI is, its applications, ethics, and where the technology is heading. Great complement to the Google and Microsoft courses.

Grant Sanderson's visually stunning series on neural networks, backpropagation, and gradient descent using animated math. No coding needed. Essential viewing before diving deeper.

Learn prompt engineering best practices for building LLM applications. Taught by Andrew Ng and Isa Fulford from OpenAI. The most popular short course on the platform.

150+ bite-sized courses (1–2 hrs each) built with Anthropic, OpenAI, Google, and AWS. Topics span agents, RAG, LLMOps, fine-tuning, and GenAI applications. All short courses are genuinely free.

Build production-ready LLM apps with LangChain — chains, agents, memory, and document Q&A. Essential for anyone building AI-powered applications.

Learn Python in the context of AI from day one. Build real AI applications using Python and LLM APIs — no prior coding experience required.

OpenAI's official free learning platform covering ChatGPT, GPTs, prompt engineering, AI for educators, and practical AI at work. Free workshops and resources.

Google's flagship ~15-hour free ML course. Covers regression, classification, neural networks, and a dedicated LLM module on transformers and prompt engineering. Recently updated.

10 comprehensive free courses: NLP, Agents, Diffusion Models, Audio, Computer Vision, Deep RL, ML for Games, MCP, and more. Community certificates included.

The definitive free course on building AI agents — from smolagents to multi-agent systems, tool use, and production deployment patterns.

Free bite-sized courses (2–8 hours) with in-browser coding and free certificates: Intro to ML, Intermediate ML, Deep Learning, NLP, Computer Vision, AI Ethics, and Python.

NVIDIA's free self-paced courses on AI, deep learning, computer vision, NLP, and data science — the same courses used to train NVIDIA engineers. Certificate included.

135+ free AWS courses covering ML fundamentals, generative AI, Amazon Bedrock, responsible AI, and more. The free tier covers all foundational content.

Multi-course IBM professional certificate covering AI fundamentals, Python for AI, NLP, computer vision, and building production AI apps. Free to audit each course.

Microsoft's central AI learning portal — modules on generative AI, Azure OpenAI, ML fundamentals, responsible AI, and prompt engineering. Prepares for Azure AI-900 certification.

The same ML courses used to train Amazon's engineers — now free to the public. Covers NLP, computer vision, tabular data, and tree-based models. Videos on YouTube + notebooks on GitHub.

Build neural networks completely from scratch — from micrograd (autograd engine) through character-level language models to a full GPT. By Tesla/OpenAI's former AI director. The single best resource for understanding how LLMs work at a mechanical level.

Top-down, code-first deep learning course used by professionals worldwide. Starts with real working models and works backward to theory. Part 2 builds diffusion models from scratch.

Andrew Ng's updated flagship ML course: supervised learning, unsupervised learning, neural networks, and ML best practices. The gold standard ML curriculum.

The foundational graduate-level ML course. Rigorous mathematical treatment of supervised, unsupervised, and reinforcement learning. Lecture videos and notes freely accessible.

The complete course for working with LLMs using the Transformers library — from tokenization and fine-tuning to building production NLP pipelines with BERT, GPT-2, and more.

The official PyTorch tutorial collection — tensors, autograd, neural network modules, computer vision, NLP, and deployment. The authoritative reference for building deep learning models.

Production-grade generative AI engineering: LLMs, RAG systems, fine-tuning, and building AI applications at scale. Free to audit all content.

Short video summaries of the latest AI research papers — making cutting-edge work accessible without reading 40-page PDFs. 1.7M+ subscribers. Essential for staying current with the field.