Best Free AI Courses
Fast.ai Practical Deep Learning — the gold standard for beginners, taught top-down so you build things immediately. Andrew Ng's Machine Learning Specialization (Coursera, free to audit) — the most famous ML course ever created. Google's Machine Learning Crash Course — concise, practical, with TensorFlow exercises. Harvard CS50 AI (edX, free to audit) — excellent introduction to AI concepts with Python. Hugging Face NLP Course — free, practical course on natural language processing with transformers.
Free Learning Platforms
Kaggle Learn — bite-sized tutorials on Python, ML, deep learning, and data science with hands-on exercises. Google Colab — free GPU access for running ML experiments in the cloud. YouTube — channels like 3Blue1Brown (visual math), Sentdex (practical Python ML), and Yannic Kilcher (paper reviews) are world-class free education. Papers With Code — read the latest research with working implementations. GitHub — thousands of open-source AI projects with tutorials and documentation.
Learning Path for Beginners
Month 1: Learn Python basics (Codecademy or freeCodeCamp — both free). Month 2: Take Andrew Ng's ML course to understand fundamentals. Month 3: Complete Fast.ai's Practical Deep Learning course to build real projects. Month 4: Do 3 Kaggle competitions to practice on real data. Month 5: Specialize in your area of interest (NLP, computer vision, or reinforcement learning). Month 6: Build a portfolio project and deploy it. This path takes you from zero to job-ready in 6 months — entirely free.
Hands-On Projects to Build
Learning AI requires building things. Start with: 1) A spam email classifier using scikit-learn. 2) An image classifier using a pre-trained model (transfer learning). 3) A chatbot using the Claude or OpenAI API. 4) A sentiment analysis tool for product reviews. 5) A recommendation system for movies or music. 6) A RAG application that answers questions about your own documents. Each project teaches different skills and looks great in a portfolio.
Free Books & Resources
'Dive into Deep Learning' (d2l.ai) — interactive textbook with runnable code. 'The Hundred-Page Machine Learning Book' — concise overview of core concepts. 'Hands-On Machine Learning' (O'Reilly) — available through most library systems. Anthropic's documentation — excellent for learning about Claude API and modern AI safety. arXiv.org — free access to every AI research paper. Distill.pub — beautifully visualized explanations of ML concepts. Visit aibot.forum for curated learning paths and community Q&A.
Recommended Resources
The aibot.* Network
- aibot.beer — Beer recommender
- aibot.coupons — AI deal finder
- aibot.courses — Course recommender
- aibot.delivery — Delivery optimizer
- aibot.directory — Business directory
- aibot.forum — AI Q&A forum
- aibot.garden — Garden planner
- aibot.gay — LGBTQ+ community
- aibot.poker — Poker analyzer
- aibot.rest — Restaurant finder
- aibot.study — AI study tutor
- aibot.tattoo — Tattoo designer