AI learning path
Choose a practical starting point, build a weekly practice rhythm, and learn AI without collecting courses you never finish.
For Beginners and career switchers
8 resources
DeepLearning.AI · Andrew Ng
A non-technical orientation to what generative AI can do, where it fails, and how teams can use it responsibly.
Microsoft
A structured, code-forward curriculum covering generative AI concepts and application building.
Google for Developers
Interactive modules on models, data, embeddings, neural networks, and production considerations.
Stephen Wolfram Writings · Stephen Wolfram
A visual, long-form attempt to explain token prediction, neural networks, training, and why fluent output is not the same as grounded correctness.
NVIDIA Deep Learning Institute
A visual introduction to generative AI concepts and practical starting points from NVIDIA's learning platform.
Google for Developers
A practical guide to deciding whether a real problem is suitable for machine learning before choosing a model or collecting data.
Andrej Karpathy · Andrej Karpathy
A creator-led programming series that builds neural-network concepts from small code examples upward.
University of Helsinki & MinnaLearn
A non-technical course that builds intuition for defining AI, search, probability, machine learning, neural networks, and societal impact through short readings and exercises.
