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tech Reading Harvard CS50 AI

Harvard CS50 AI Week 2: Uncertainty — Probability, Bayesian Networks, Markov Models & Genetic Inference

Week 2 shifts from deterministic to probabilistic: Bayes rule, Bayesian nets with D-separation, Markov chains, PageRank random walks. Projects: Heredity (genotype inference) and PageRank (web ranking).

#harvard-cs50ai#ai#probability#bayesian-network#markov-model#heredity#pagerank#python#cs50
learning guide Berkeley CS188 Spring 2026

CS188 Bayes Nets and Ghostbusters: Inference When Ghosts Are Invisible

Lectures 13–18 and Project 4 move from factor operations and variable elimination to exact inference and particle filtering, letting Pacman track invisible ghosts through noisy distance sensors.

#berkeley#cs188#bayesian-network#probabilistic-inference#particle-filter
ai deep-dive Reading Stanford CS228

Stanford CS228: The Prerequisites Are One Sentence About Probability and Algorithms — But the Course Hasn't Run in Two Years

CS228's official prerequisite is a single line — 'basic probability theory and algorithm design and analysis' — with no named course. But ExploreCourses shows it was last offered in Winter 2024, and the next slot, Winter 2027, still has a blank instructor field. What a self-learner can actually get is cs228-notes: 16 chapters, complete, last touched in June 2025.

#cs228#ai-course#stanford#probabilistic-graphical-models#bayesian-network#variational-inference