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	Lecture	Assignment	Exam
Sept. 9	Defining AI		-	-
Sept. 14	Intro to machine learning (ML)		-	-
Sept. 16	Learning Algorithms		-	-
Sept. 21	Linear regression and gradient descent		-	-
Sept. 23	Logistic regression		-	-
Sept. 28	Logistic Regression: Cross-Entropy and Geometry		-	-
Sept. 30	Performance evaluation		-	-
Oct. 5	Model Evaluation and Hyperparameter Tuning		-	-
Oct. 5	-	-	A1: Jupyter	-
Oct. 7	-	-	-	Quiz
Oct. 12	Thanksgiving - no lecture	-	-
Oct. 14	Machine Learning Engineering		-	-
Oct. 19	Introduction to Artificial Neural Networks		-	-
Oct. 21	Implementing Artificial Neural Networks (Part 1)		-	-
Oct. 26	-	-	A2: ML	-
Oct. 26	Reading week - no lecture	-	-	-
Oct. 28	Reading week - no lecture	-	-	-
Nov. 2	-	-	A2: ML	-
Nov. 2	Implementing Artificial Neural Networks (Part 2)		-	-
Nov. 4	Training neural networks: challenges and practical choices		-	-
Nov. 9	Neural Network Architectures		-	-
Nov. 11	Introduction to Search		-	-
Nov. 16	Informed Search		-	-
Nov. 16	-	-	A3: DL	-
Nov. 18	-	-	-	Quiz
Nov. 23	Local Search		-	-
Nov. 25	Population-Based Metaheuristics		-	-
Nov. 30	Population-Based Metaheuristics (continued)		-	-
Dec. 2	Adversarial Search		-	-
Dec. 7	Monte Carlo Tree Search		-	-
Dec. 9	Monte Carlo Tree Search (continued)		-	-
Dec. 9	-	-	A4: Search	-