Artificial Intelligence
Search, logic, planning and reasoning under uncertainty.
Intelligent Agents & Problem Formulation
AI is the science of building agents that perceive the world and act rationally to achieve goals — and this module shows you exactly how to think about that, rigorously.
Uninformed & Informed Search
Master the art of navigating state spaces — from blind BFS/DFS through the elegant optimality guarantees of A* — and understand exactly why and when each algorithm finds the shortest path.
Adversarial Search & Games
From tic-tac-toe to chess engines: how adversarial search turns combinatorial game trees into optimal decisions through minimax, alpha-beta pruning, and probabilistic rollouts.
Constraint Satisfaction Problems
Constraint Satisfaction Problems transform combinatorial puzzles into a structured search through variable assignments, where smart propagation and ordering can slash exponential costs to near-linear.
Logic & Knowledge Representation
Logic gives AI a language for thought — first-order logic, resolution, and knowledge bases are the bedrock on which machines can reason, prove, and know.
Planning
Classical planning transforms the dream of "act rationally toward goals" into precise algorithms — turning goal-directed intelligence from philosophy into computable reality.
Probabilistic Reasoning & Bayesian Networks
Master the mathematics of belief under uncertainty — Bayesian networks, exact and approximate inference, hidden Markov models, and Kalman filters — the probabilistic backbone of every serious AI system.
Markov Decision Processes
MDPs give you the mathematical language to turn "act wisely under uncertainty over time" into a precise optimization problem — and solve it exactly.