AI & Machine Learning: Zero to Expert
A complete path from zero to expert: Python, math, machine learning, deep learning, LLMs, agents and production. Free resources first, with paid courses and books listed separately.
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By the end of this phase
You can explain AI, ML and deep learning to a friend, and you know where AI helps and where it fails.
AI vs ML vs Deep Learning
Think of a Russian nesting doll: AI is the big outer doll (making computers smart). ML is the middle doll (learning from data, not hard-coded rules). Deep Learning is the innermost doll (neural networks inspired by the brain).
Narrow AI vs General AI (AGI)
Everything we have today is Narrow AI — great at specific tasks (faces, chess, text). AGI is the idea of a machine as capable as a human across everything. Know the difference so you can separate hype from reality.
A Brief History of AI
AI has had multiple 'winters' and 'summers'. The history explains why deep learning took off in the 2010s and why transformers changed everything in 2017.
Ethics & Bias in AI
AI learns from human data. If the data has biases (racial, gender, socioeconomic), the AI copies them. Fairness and ethics matter as much as the technical skills.
AI Around Us — Where Do We See It?
Before you build AI, recognize it: Netflix recommendations, Google Translate, Spotify Discover Weekly, your phone's face unlock. AI is already everywhere — try a few for yourself.
How to Learn Effectively (Your Study System)
Learning AI is a long game. Use active recall, spaced repetition and build-as-you-learn. Set a weekly schedule, keep notes, and ship a tiny project every phase.