AI: Lectures

University of Illinois

Lecture and Collab Schedule

Lecture videos will be uploaded to mediaspace by 13:00 on the dates specified. Readings and sample problems are from Russell and Norvig unless specified.

Date Topics (R)eadings &
Assignment Due
M 1/25 Intro (PPT, PDF) R1.1,2.3 (P2.3)
W 1/27 Search (PPT, PDF) R3.1,3(P3.1-3,8,10-13)
M 2/1 A* (PPT, PDF) R3.4.1-3(P3.14-16)
W 2/3 Heuristics (PPT, PDF) R3.5.1-2,3.6(P3.21,23,26-29,31)
MWF Collab 1
M 2/8 Probability (PPT, PDF) R12.1-5
W 2/10 Naive Bayes (PPT, PDF) R12.6 MP1
Wed, Fri Collab 2
M 2/15 Classifiers (PPT, PDF) R19.2,19.6
Mon Collab 2
W 2/17 No Lecture, No Collab
Fri Collab 3
M 2/22 Perceptron (PPT, PDF) R21.1,3-5
W 2/24 Logistic Regression (PPT, PDF) JM5 MP2
Mon, Wed Collab 3
Fri Collab 4
M 3/1 Back-Propagation (PPT, PDF) JM7.1-4
W 3/3 Exam 1 Review (PPT, PDF)
Mon, Wed Collab 4
F 3/5 Exam 1 Exam 1
M 3/8 Autograd (PPT, PDF) Pytorch tutorial
W 3/10 Bayes Nets (PPT, PDF) R13.1-5
MWF Collab 5
M 3/15 Bayes Nets (PPT, PDF) Charniak Bayes Nets
W 3/17 HMMs (PPT, PDF) R14.1-3 MP3
Wed, Fri Collab 6
M 3/22 Viterbi Algorithm (PPT, PDF) JM8.1-4
Mon Collab 6
W 3/24 No Lecture, No Collab
Fri Collab 7
M 3/29 Vector semantics (PPT, PDF) JM6
W 3/31 Minimax Games (PPT, PDF) R5.1-5 MP4 (HMM)
Mon, Wed Collab 7
Fri Collab 8
M 4/5 Alpha-Beta Search (PPT, PDF)
W 4/7 Exam 2 Review (PPT, PDF)
Mon, Wed Collab 8
F 4/9 Exam 2 Exam 2
M 4/12 Game Theory (PPT, PDF) R18.1-3
W 4/14 Markov Decision Processes (PPT, PDF) R17.1-3
MWF Collab 9
M 4/19 Model-Based RL (PPT, PDF) R22.1-7 MP5 (games)
W 4/21 Model-Free RL (PPT, PDF)
MWF Collab 10
M 4/26 AI Ethics (PPT, PDF) R26.3
W 4/28 Computer Vision (PPT, PDF) R25.4 MP6 (RL)
MWF Collab 11
M 5/3 Exam 3 Review (PPT, PDF)
F 5/7 Final Exam 13:30-16:30 Final Exam
F 5/7 or T 5/11 Conflict Final Exam 8:00-11:00 Conflict Final