CS 431: Introduction to Artificial Intelligence

Syllabus

You can download the syllabus here. The syllabus includes information on grading, course goals, and policies I will use in teaching this course.

Text

Géron

We will be using Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow by Aurélien Géron. This is more of a reference book than a traditional textbook, that you will be able to use after you have graduated.

Homework

There will be five homework assignments over the course of the semester. They will be large—please allot them plenty of time. General specifications for your work can be found here.

Class Schedule

This is a tentative schedule for the class. I may change it depending on how the class progresses.

WeekDatesReadingsHomeworkFilesDue Date
1Jan. 16 - 19 Python Tutorial
“Humans Need Not Apply”
2Jan. 22 - 26
3Jan. 29 - Feb. 2 Sliding Puzzleslidingpuzzle.py
easy.puz
square.puz
impossible.puz
Feb. 11
4Feb. 5 - 9
5Feb. 12 - 16 “The Man vs. The Machine”
6Feb. 19 - 23 Chapters 1 - 3
Chess’s New Best Player...
“The Evolution of Trust”
Connect Fourconnect4.py
connect4player.py
Feb. 25
7Feb. 26 - March 1 Chapter 6
8March 4 - 8 Chapter 10
“How Machines Learn”
Midterm: Week 8
Spring Break!
9March 18 - 22 Chapter 11 Decision Treesvoting-data.tsvMarch 24
10March 25 - 29
11April 1 - 5 Chapter 14
12April 8 - 12 Google Blog: Inceptionism... Convolutional Neural Networks(see class-only page)April 7
13April 15 - 19 Chapter 9
14April 22 - 24 k-MeansApril 28
Final Exam: Friday, May 12, 4:00

Projects

Projects are due at the end of class. Click here for some ideas.

Class-Only Information

Click here if you’re in the class, for more useful information.

Other Resources

Any other useful resources will be put here.