Index

Homework and Grading

Lectures (Hasegawa-Johnson)

Lectures (Hockenmaier)

Internship Opportunities

Compass2g

Piazza

Videos

  1. T Jan 15: Intro to AI
    Reading: Ch. 1
    Slides: pdf.
  2. R Jan 17: History of AI
    Reading: Ch. 1
    Slides: pdf.
  3. T Jan 22: Agents Reading: Ch. 2
    Slides: pdf.
    Assignment 1 published
  4. R Jan 24: Uninformed Search: Tree Search, including BFS, DFS, IDS
    Reading: Sec. 3.1-3.2
    Slides: pdf.
  5. T Jan 29: Informed Search: Greedy, A*
    Reading: Sec. 3.3-3.6
    Slides: pdf.
  6. R Jan 31: Constraint Satisfaction Problems Reading: Ch. 6
    Slides: pdf.
    Assignment 1 due M Feb 4
  7. T Feb 5: Planning
    Reading: Ch. 10
    Assignment 2 published
    Slides: pdf.
  8. R Feb 7: Two-Player Games
    Reading: Ch. 5
    Slides: pdf.
  9. T Feb 12: Game Theory
    Slides: pdf.
  10. R Feb 14: Probability
    Reading: Ch. 13, Recommended Problems: 13.1-12, 16.3
    Slides: pdf.
  11. T Feb 19: Random Variables
    Reading: Ch. 13
    Slides: pdf.
  12. R Feb 21: Stochastic Games, Imperfect Information, and Stochastic Search
    Reading: Sec. 17.5-17.6
    Slides: pdf.

    13. Assignment 2 due M Feb 25
  13. T Feb 26: Exam 1 Review
    Review 1
  14. R Feb 28: Exam 1 (in class)
  15. T Mar 5: Bayesian Inference and Bayesian Learning
    Reading: Ch. 13, Recommended Problems: 13.13-24, 18.18, 20.9; repeat 13.22 using Laplace smoothing
    Slides: pdf.

    16. Assignment 3 published
  16. R Mar 7:Linear Dichotomizers: Bayesian, Perceptron, Logistic Regression
    Reading: Sections 18.6-18.7, Recommended Problems: 18.16,20,21,23,25; 20.4
    Slides: pdf.
  17. T Mar 12: Linear and PWL Polychotomizers: Perceptron, Softmax, KNN
    Reading: Sections 18.6-18.7, Recommended Problems: 18.19,22
    Slides: pdf.
  18. R Mar 14: More on classification
    Reading: Ch. 14, Recommended Problems:
    Slides: pdf.
  19. T Mar 26: Bayesian Networks and Bayes Net Inference
    Reading: Ch. 20, Recommended Problems: 14.15-16,20.1-3,20.6,20.8,20.10, 14.1-8,11-14;16.5,16.17

    20. Slides: pdf.
  20. R Mar 28: Hidden Markov Models
    Reading: Ch. 15, Recommended Problems: 15.1-6,13-17
    Assignment 3 due M Apr 1 Slides: pdf.
  21. T Apr 2: Markov Decision Processes
    Reading: Ch. 17, Recommended Problems: 17.1-10
    Assignment 4 published pdf.
  22. R Apr 4: Reinforcement Learning
    Reading: Ch. 21, Recommended Problems: 22.2,4,6,8
    23. pdf.
  23. T Apr 9: Deep Learning
    Slides: pptx, pdf.
  24. R Apr 11: Deep Reinforcement Learning
    Slides: pptx, pdf.
  25. T Apr 16: Natural Language Processing
    Slides: pptx, pdf.
  26. R Apr 18: Speech
    Assignment 4 due M Apr 22
    Slides: pptx, pdf.
  27. T Apr 23: Societal Impacts of AI
    Slides: pptx, pdf.
  28. R Apr 25: Exam 2 Review
    Slides: pdf.
  29. T Apr 30: Exam 2 Review
    Slides: pdf.
  30. Exam 2: Monday, May 6, 9:30-10:45am, MatSEB 100