COMP560: Artificial Intelligence
Logistics
When: Tuesdays and Thursdays, 11:00 am-12:15 pm
Where: FB-009
Office hours:
Instructor: 12:30-1:30 Thu in Sitterson 235 (email for appt)
TA: 3-4 Wed in Sitterson 137, or online at https://unc.zoom.us/j/5456744738 . You can email jleung18@cs.unc.edu for office hour appointments outside this times
Sign up on the course Piazza (Access code is comp560)
Announcements:
Assignment 1 is out (due on Feb 14)
Assignment 2 is out (due on Mar 19)
Assignment 3 is out (due on April 15)
Assignment 4 is out (due on April 30)
Some sample project ideas.
People
Instructor
Shashank Srivastava
ssrivastava@cs.unc.edu
Teaching Assistant
Johnathan Leung
jleung18@cs.unc.edu
Course Information
This course will explore foundational topics and techniques in Artificial Intelligence, as well as sample some applications and areas of active research. The first part of the course will cover classical topics such as search and constraint satisfaction. The second part of the course will delve into probabilistic graphical models and inference methods, necessary skills for handling uncertainty in AI systems. The third part will touch on the basics of machine learning and neural networks, with a more focused exploration of Reinforcement Learning. The list of tentative topics is:
Search methods
Constraint satisfaction
Probabilistic graphical models
Probabilistic inference
Decision theory
Neural networks & ML basics
Reinforcement Learning
Ethics and biases in AI
The course will be at an advanced undergraduate/beginner graduate level. The course will presume a functional understanding of probability, statistics, linear algebra, and specific CS topics such as Dijkstra's algorithm. The assignments and project will have substantial programming components.
