Assignments
Date  Topic 

Week 1 Jan 10, 12 
Introduction, AI EthicsReading: due Monday 1/9, 5:00 pm

Week 2 Jan 17, 19 
SearchReading: due Monday 1/16, 5:00 pm

Week 3 Jan 24, 26 
Constraint Satisfaction Problems and Local SearchReading: due Monday 1/23, 5:00 pm

Week 4 Feb 7, 9 
Adversarial Search, UtilitiesReading: due Monday 2/6, 5:00 pm

Week 5 Feb 14, 16 
Markov Decision ProcessesReading: due Monday 2/13, 5:00 pm

Week 6 Feb 21, 23 
Reinforcement Learning, ProbabilityReading: due Monday 2/20, 5:00 pm

Week 7 Feb 28, Mar 2 
Bayes Nets: Representation, IndependenceReading: due Monday 2/28, 5:00 pm

Week 8 Mar 7, 9 
Bayes Nets: Inference, MidtermMidterm exam:

Week 9 Mar 21, 23 
Bayes Nets: Sampling, (Hidden) Markov ModelsReading: No reading due this week. Homework: due Monday 4/10, 11:59 pm

Week 10 Mar 28, 30 
Particle Filters, Decision NetworksReading: due Monday 3/27, 5:00 pm

Week 11 Apr 4, 6 
Naive Bayes, Perceptrons, ClusteringReading: due Monday 4/3, 5:00 pm

Week 12 Apr 11, 13 
Guest Lecture, Deep LearningGuest speaker: Prof. Bruce Porter, UT Austin and SparkCognition Reading: due Monday 4/10, 5:00 pm

Week 13 Apr 18, 20 
Guest Lecture II, ConclusionGuest speaker: Dr. Jim Fan, NVIDIA Research Reading: due Monday 4/17, 5:00 pm

Final Exam Apr 28, 810 am 
Final ExamLocation: GEA 105 