| A | B | C | D | E | F | G | H | I | J | |
|---|---|---|---|---|---|---|---|---|---|---|
1 | Date | Topic | Reading | Homework | Exam Coverage | Quiz Coverage | ||||
2 | 1 | Sun | Mehr 1 | Introduction & Intelligent Agents | Ch.1, Ch.2 | HW1 | M | |||
3 | 2 | Tue | Mehr 3 | Uninformed Search | Ch. 3 | HW1 | M | |||
4 | 3 | Sun | Mehr 8 | Uninformed Search | Ch. 3 | HW1 | M | |||
5 | 4 | Tue | Mehr 10 | Informed Search | Ch. 3 | HW1 | M | |||
6 | Sat | Mehr 14 | HW1 Release | |||||||
7 | 5 | Sun | Mehr 15 | Informed Search | Ch. 3 | HW1 | M | |||
8 | 6 | Tue | Mehr 17 | Local Search | Ch. 4.1 | HW1 | M | |||
9 | 7 | Sun | Mehr 22 | Search in Continuous spaces | Ch. 4.2 | HW2 | M | |||
10 | 8 | Tue | Mehr 24 | Constraint Satisfaction Problems I | Ch. 6 | HW2 | M | |||
11 | Fri | Mehr 27 | HW1 Deadline | |||||||
12 | Sat | Mehr 28 | HW2 Release | |||||||
13 | 9 | Sun | Mehr 29 | Constraint Satisfaction Problems II | Ch. 6 | HW2 | M | |||
14 | 10 | Tue | Aban 1 | Adversarial Search | Ch. 5 | HW2 | M | |||
15 | 11 | Sun | Aban 6 | Uncertainty & Inference | Ch. 12, Ch. 13 | HW3 | M | |||
16 | 12 | Tue | Aban 8 | Bayesian Networks: Representation | Ch. 12, Ch. 13 | HW3 | M | |||
17 | 13 | Sun | Aban 13 | Inference in Bayesian Networks: Exact | Ch. 12, Ch. 13 | HW3 | M | |||
18 | Mon | Aban 14 | HW2 Deadline | |||||||
19 | 14 | Tue | Aban 15 | Inference in Bayesian Networks: Approximate | Ch. 12, Ch. 13 | HW3 | M | |||
20 | 15 | Sun | Aban 20 | Temporal Probability Models: Markov Chains & HMMs | Ch. 14 | HW3 | M | |||
21 | 16 | Tue | Aban 22 | Temporal Probability Models: Particle Filters | Ch. 14 | HW3 | M | |||
22 | Sat | Aban 26 | HW3 Release | |||||||
23 | 17 | Sun | Aban 27 | Learning in Bayesian Networks & Naive Bayes | Ch. 19 | HW4 | F | |||
24 | 18 | Tue | Aban 29 | Decision Tree | Ch. 19 | HW4 | F | |||
25 | 19 | Sun | Azar 4 | Concepts of Machine Learning | Ch. 19 | HW4 | F | |||
26 | 20 | Tue | Azar 6 | Regression & Optimization | Ch. 19 | HW4 | F | |||
27 | Fri | Azar 9 | HW3 Deadline | |||||||
28 | 21 | Sun | Azar 11 | Perceptron | Ch. 21 | HW4 | F | |||
29 | 22 | Tue | Azar 13 | Neural Networks I | Ch. 21 | HW4 | F | |||
30 | Sat | Azar 17 | HW4 Release | |||||||
31 | 23 | Sun | Azar 18 | Neural Networks II | Ch. 21 | HW4 | F | |||
32 | 24 | Tue | Azar 20 | Markov Decision Process | Ch. 17 | HW5 | F | |||
33 | Thu | Azar 22 | Midterm | |||||||
34 | 25 | Sun | Azar 25 | Markov Decision Process: Value Iteration & Policy Iteration | Ch. 17 | HW5 | F | |||
35 | 26 | Tue | Azar 27 | Reinforcement Learning: Passive | Ch. 22 | HW5 | F | |||
36 | 27 | Sun | Dey 2 | Reinforcement Learning: Active | Ch. 22 | HW5 | F | |||
37 | Mon | Dey 3 | HW4 Deadline | |||||||
38 | 28 | Tue | Dey 4 | Reinforcement Learning: Approximate | Ch. 22 | HW5 | F | |||
39 | Sat | Dey 8 | HW5 Release | |||||||
40 | 29 | Sun | Dey 9 | Applications / Guest Lecturer | - | - | - | - | ||
41 | 30 | Tue | Dey 11 | Applications / Guest Lecturer | - | - | - | - | ||
42 | Fri | Dey 21 | HW5 Deadline | |||||||
43 | Sun | Dey 30 | Final Exam | |||||||
44 | ||||||||||