# Schedule


Week Date Topics E M P
W1 02-Jun Perceptron Algorithm E1 M1 P1
03-Jun Logistic Regression E2 M2
04-Jun Neural Network E3 M3
05-Jun Backpropagation E4
W2 09-Jun Support Vector Machine E5 M4 P2
10-Jun K-Nearest-Neighbors, Decision Tree E6
11-Jun Computer Vision E7 M5
12-Jun Deep Learning, Convolutional Network E8
W3 16-Jun Natural Language and Speech E9 M6 P3
17-Jun Naive Bayes, Bayesian Network E10
18-Jun Hidden Markov Model E11 M7
19-Jun Recurrent Neural Network E12
W4 23-Jun Markov Decision Process E13
24-Jun Reinforcement Learning E14
25-Jun Midterm Review, Part I P6
26-Jun Midterm Review, Part II
W5 30-Jun Midterm Exam, Part I
01-Jul Midterm Exam, Part II
02-Jul Hierarchical Clustering, K-Means Clustering E15 M8 P4
03-Jul Principal Component Analysis E16
W6 07-Jun Uninformed Search, Robotics E17 M9 P5
08-Jul Informed Search E18
09-Jul Hill-Climbing, Simulated Annealing E19 M10
10-Jul Genetic Algorithms, Constraint Satisfaction E20
W7 14-Jul Game Theory E21 M11
15-Jul Minimax Game, Alpha-Beta Pruning E22 M12
16-Jul Repeated Games E23
17-Jul Mechanism Design E24
W8 21-Jul Final Review, Part I P6
22-Jul Final Review, Part II
23-Jul Final Exam, Part I
24-Jul Final Exam, Part II


📗 Click the W1, W2, etc to see the lecture slides and the links to the lecture examples (E), math homework (M), and programming homework (P) of the week.
📗 Lecture recordings will be posted on YouTube, and the links will be posted on this website. Official lecture times will be used for brief reviews, going over examples, and quizzes, on Canvas BBCollaborateU, not recorded.
📗 The topics are subject to change.
📗 The optional textbooks are (RN) Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig Link and (SS) Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Schwartz and Shai Ben-David Link.
📗 Any edition of RN is okay. SS is freely available online. No homework problem will be assigned from the textbooks. For students planning to take CS760 and CS761, SS is highly recommended.

# Grading Scheme


Component Frequency Number Max Points Each
Quizzes Daily 20 1
Math (Written) Weekly 10 2
Programming Weekly 5 8
Midterm Once 1 10
Final Once 1 10


📗 The recommended programming language is Java and Python. Code written in other languages will be accepted. The course staff will only be able to provide help with code in Java and Python.
📗 The lowest 4 quiz and 2 math homework grades out of 24 or 12 are dropped. If you cannot attend any of the quizzes due to scheduling conflicts, your midterm and final exam grades will count for 20 points each. If you cannot attend some of the quizzes, you can use the extra math (two of them) and programming homework (one of them) grades to replace those too.
📗 The lowest programming homework grade can be replaced by a programming project you choose (P6): the project must implement at least one of the algorithms covered during the lecture on a dataset of your choice.

Grade Letter Numeric
90+ A 4
85+ AB 3.5
80+ B 3
75+ BC 2.5
70+ C 2
60+ D 1
0+ F 0


📗 The conversion table is subject to minor modification.
📗 Midterm and final exam grades will be curved by dropping the questions with a negative point biserial correlation coefficient (RPBI < 0) or less than a quarter of the students answered correctly (PROB < 25%). The students who answered those correctly keep the points as bonus points. Quiz and homework grades will not be curved. The final grade will not be curved.

Exams Time Format Coverage
Midterm 2 hours 20 Short Answer W1 to W3
Final 2 hours 20 Short Answer W5 to W7


# Admin


📗 TA: Ainur Ainabekova
📗 Office Hours: Tuesdays 5:00 to 6:00 for Programming Homework related questions

📗 TA: Dandi Chen
📗 Office Hours: Thursdays 5:00 to 6:00 for Math Homework related questions

📗 Instructor: Young Wu
📗 Office Hours: Tuesdays, Wednesdays, Thursdays, Fridays after lecture.

# Course Website


📗 This webpage (for lecture notes and assignments).
📗 Summer 2019 Course: 2019.
📗 Canvas (for grades): Link.
📗 Piazza (for discussion): Link.
📗 Socrative (for quizzes): Link. The room numbers are "CS540C" for graded quizzes and "CS540" for anonymous feedback: use your wisc ID to log in. You can also use the following room links: CS540C or yCS540.
📗 Professor Jerry Zhu: 2020.
📗 Professor Yingyu Liang: 2018 and 2019
📗 Professor Charles Dyer: 2019;
📗 Professor Jude Shavlik: 2016.






Last Updated: July 14, 2024 at 8:38 PM