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Schedule (Spring 2016)

Credit

This course closely follows the UC Berkeley CS188 course. We gratefully acknowledge all course materials freely provided by Dan Klein and Pieter Abbeel.

Week 1

  • Introduction [Lecture] - Jan 26
  • Search, State Spaces, and DFS [Lecture] - Jan 28

Week 2

  • BFS and Uniform Cost [Lecture] - Feb 2
  • Informed Search (A*) [Lecture] - Feb 4
  • Math Self Diagnostic Due Feb 4

Week 3

  • A* Analysis [Lecture] - Feb 9
  • P0: Python Due Feb 9
  • CSP I: Definition, Backtracking [Lecture] - Feb 11
  • HW1: Search Due Feb 11

Week 4

  • CSP II: Forward Checking, Arc Consistency [Lecture] - Feb 16
  • CSP III: Ordering, Structure, Local Search [Lecture] - Feb 18
  • P1: Search Due Feb 18

Week 5

  • Adversarial Search: Minimax, Alpha Beta Pruning [Lecture] - Feb 23
  • Adversarial Search: Stochastic Games [Lecture] - Feb 25
  • HW2: CSPs Due Feb 25

Week 6

  • Utilities [Lecture] - Mar 1
  • MDPs I [Lecture] - Mar 3
  • HW3: Games Due Mar 3
  • C1: Search Due Mar 3

Week 7

Week 8

  • Midterm Exam (3:30-4:45p) -Mar 15
  • HW4: MDPs Due Mar 15
  • Reinforcement Learning I [Lecture] - Mar 17
  • P2: Multi-Agent Search Due Mar 17

Week 9

  • Spring Break - Mar 22
  • Spring Break - Mar 24

Week 10

  • Reinforcement Learning II [Lecture] - Mar 29
  • C2: Multi-Agent Search Due Mar 29
  • Reinforcement Learning III [Lecture] - Mar 31

Week 11

  • Probability Review [Lecture] - Apr 5
  • HW5: Reinforcement Learning Due Apr 5
  • Naive Bayes [Lecture] - Apr 7

Week 12

  • Perceptron [Lecture] - Apr 12
  • P3: Reinforcement Learning Due Apr 12
  • Class cancelled - Apr 14

Week 13

  • kNN and Clustering [Lecture] - Apr 19
  • HW6: Machine Learning Due Apr 19
  • Computer Vision and Machine Learning [Lecture] - Apr 21

Week 14

  • Loss Functions and Optimization [Lecture] - Apr 26
  • P4: Classification Due Apr 26
  • Backpropagation and Neural Networks [Lecture] - Apr 28

Week 15

  • Final Exam (3-6p) - May 5