Introduction to Artificial Intelligence
AI is not magic — it is math, history, and human choice. We build from first principles: probability, search, neural networks, language models. Then we ask who built these systems, for whom, and what they're encoding about the world.
Introduction to Artificial Intelligence
AI is not magic — it is math, history, and human choice. We build from first principles: probability, search, neural networks, language models. Then we ask who built these systems, for whom, and what they're encoding about the world.
Understand AI from first principles: probability, logic, linear algebra
Build each major AI concept from scratch before using libraries
Critically analyze who built AI systems, who benefits, and who is harmed
Implement search algorithms, neural networks, and NLP pipelines
Conduct a structured bias audit of a real deployed AI system
Communicate technical AI concepts to non-technical audiences
Develop a portfolio demonstrating deep understanding
First Principles First — understand every layer before stacking them
Choose Your Adventure — three tracks, diverge on projects
Liberation Through Understanding — critical consciousness is the most advanced technical skill