CSI 4106: Introduction to Artificial Intelligence

This page contains an outline of the topics, content, and assignments for the semester.

Note that this schedule will be updated as the semester progresses, with all changes documented here.

Date	Topic	Prepare	Slides	Assignment	Exam
Sept. 3	Defining AI			-	-
Sept. 8	Intro to machine learning (ML)			-	-
Sept. 10	Learning Algorithms			-	-
Sept. 15	Linear regression and gradient descent			-	-
Sept. 17	Logistic regression			-	-
Sept. 22	Cross-entropy, geometric interpretation			-	-
Sept. 24	Performance evaluation			-	-
Sept. 29	Model Evaluation and Hyperparameter Tuning			-	-
Sept. 29	-	-	-	A1: Jupyter	-
Oct. 1	-	-	-	-	Quiz
Oct. 6	Machine Learning Engineering			-	-
Oct. 8	Introduction to Artificial Neural Networks			-	-
Oct. 13	Reading week - no lecture	-	-	-	-
Oct. 15	Reading week - no lecture	-	-	-	-
Oct. 20	Training Artificial Neural Networks (Part 1)			-	-
Oct. 22	-	-	-	A2: ML	-
Oct. 22	Training Artificial Neural Networks (Part 2)			-	-
Oct. 27	Sofmax, cross-entropy and regularization			-	-
Oct. 29	Convolutional Neural Networks			-	-
Nov. 3	Introduction to Search			-	-
Nov. 5	Informed Search			-	-
Nov. 10	Local Search			-	-
Nov. 10	-	-	-	A3: DL	-
Nov. 12	-	-	-	-	Quiz
Nov. 17	Population-Based Metaheuristics			-	-
Nov. 19	Adversarial Search			-	-
Nov. 24	Monte Carlo Tree Search			-	-
Nov. 26	Formal Reasoning			-	-
Dec. 1	Neuro-symbolic AI (NSAI)			-	-
Dec. 1	-	-	-	A4: Search	-