CSCE-420
Introduction to AI

Spring 2025

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Participation

Registered students must participate in online quizzes available on the course's Canvas page, as well as complete the assigned programming assignments.

Students are encouraged to attend lectures in person at HRBB 124, on Tuesdays and Thursdays from 11:10 AM to 12:25 PM. Video recordings of the lectures will be accessible under Lecture Slides.

For general questions, comments, and discussions, please use Campuswire (enrollment code: 3982). Avoid sending general queries to course staff via email, as you will be directed to the Campuswire discussion board. Assist your fellow students with posted issues---extra credit will be awarded to exceptionally helpful participants.


Text Books

  • Artificial Intelligence: A Modern Approach
  • Reinforcement Learning: An Introduction
  • Deep Learning

Lectures

Lecture #SlidesLecture
1Introduction.pptx1/14/2024
2Uninformed Search.pptx1/16/2024
3Snow Day - No Class1/21/2024
4Uninformed Search.pptx (continue)1/23/2024
5Informed Search.pptx1/28/2024
6Informed Search.pptx (continue)1/30/2024
7Adversarial Search.pptx2/4/2024
8Adversarial Search.pptx (continue)2/6/2025
9Expectimax.pptx2/11/2025
10Game Theory.pptx2/13/2025
11Game Theory.pptx (continue)2/18/2025
12MDPs.pptx2/20/2025
13MDPs.pptx (continue)2/25/2025
14Policy Iteration.pptx2/27/2025
15Reinforcement Learning.pptx3/4/2025
16Special AI Lecture.pptx3/6/2025
17Reinforcement Learning 2.pptx3/18/2025
18Midterm Practise Session3/20/2024
19Midterm Exam3/25/2024
20Reinforcement Learning 2.pptx (continue)3/27/2025
21Probabilities.pptx4/1/2025
22Bayes Nets.pptx4/3/2025
23Decision Diagrams.pptx4/8/2025
24Hidden Markov Models.pptx4/10/2025
25Particle Filtering.pptx4/15/2025
26Naive Bayes.pptx4/17/2025
27Decision Trees.pptx4/22/2025
28Neural Nets.pptx4/24/2025

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