Schedule

Please note that the items on this page are subject to change.

Date Topic Subtopic Section Readings Beyond Section HW Release HW Deadline
Week 0
Jan. 17 (Tu) HW 0 released (pre-requisites)
Jan. 19 (Th)
Jan. 20 (Fr)
Week 1 Math, Statistics, and Code Review
Jan. 24 (Tu) Intro to CS 181
Jan. 26 (Th) Regression Regression HW 1 released (regression) HW 0 due (note: free, no-questions-asked extension to Feb 2)
Jan. 27 (Fr) AI and Broader Impact
Week 2 Regression
Jan. 31 (Tu) Probabilistic Regression
Feb. 2 (Th) Confidence and Uncertainty
Feb. 3 (Fr) Kernels
Week 3 Classification
Feb. 7 (Tu) Classification Probabilistic Classification
Feb. 9 (Th) Non-Probabilistic Classification HW 2 released (classification) HW 1 due
Feb. 10 (Fr) OOD, Uncertainty, and Interpretability
Week 4 Neural Network Architectures and Optimization
Feb. 14 (Tu) Neural Networks (NN) Intro to NN
Feb. 16 (Th) More on NN
Feb. 17 (Fr) NN Interpretability
Week 5 Conjugate Pairs in Modeling
Feb. 21 (Tu) Bayesian Modeling Intro to Bayesian Models
Feb. 23 (Th) More on Bayesian Models HW 3 released (neural networks and Bayes) HW 2 due
Feb. 24 (Fr) Deep Bayes
Week 6 Midterm I Review
Feb. 28 (Tu) Bayesian Inference
Mar. 2 (Th) Practical Practical I Content Practical I released (modeling)
Mar. 3 (Fr) Advanced Sampling and Variational Inference
Week 7 Case Studies in AI and Ethics
Mar. 7 (Tu) Midterm I
Mar. 9 (Th) Ethics Embedded Ethics Lecture
Mar. 10 (Fr)
Week 8
Mar. 14 (Tu) Spring Break!
Mar. 16 (Th) Spring Break!
Mar. 17 (Fr) Spring Break!
Week 9 Dimensionality Reduction and PCA
Mar. 21 (Tu) Dimensionality Reduction Dimensionality Reduction
Mar. 23 (Th) Latent Variable Models Latent Variable Models and Expectation Maximization (EM) HW 4 released (latent variables and EM) HW 3 and Practical I due
Mar. 24 (Fr) Variational Autoencoders (VAE)
Week 10 EM
Mar. 28 (Tu) Clustering Clustering
Mar. 30 (Th) Topic Models Topic Models
Mar. 31 (Fr) Representation Learning
Week 11 Time Series
Apr. 4 (Tu) Graphical Models Graphical Models and Hidden Markov Models (HMM)
Apr. 6 (Th) Inference of HMMs HW 5 released (HMM) HW 4 due
Apr. 7 (Fr) Nonlinear Dynamics
Week 12 Defining Markov Decision Processes (MDPs)
Apr. 11 (Tu) HMMs and Learning
Apr. 13 (Th) Markov Decision Processes (MDPs) MDPs
Apr. 14 (Fr) Reinforcement Learning vs. Bandits
Week 13 Reinforcement Learning (RL) Algorithms
Apr. 18 (Tu) Reinforcement Learning (RL) Model-Based RL
Apr. 20 (Th) Model-Free RL Practical II released (RL and social-technical systems) HW 5 due
Apr. 21 (Fr) Open Problems in RL
Week 14 Midterm II Review
Apr. 25 (Tu) Practical II Content
Apr. 27 (Th) Midterm II
Apr. 28 (Fr) ML Research Beyond 181 Practical II due end of Reading Period (May 3)