This course is about the theory and practice of Artificial Intelligence and Machine Learning. We will study modern techniques to help computers learn how to make intelligent decisions using data. Note: Programming and basic English presentation skills are required.
Week1: Introduction Week2: Overview of AI history & Industry Applications Week3: Uninformed Search Week4: Informed Search Week5: Probability and Information Theory Week6: Probability and Information Theory Week7: Machine Learning Basics Week8: Machine Learning Basics Week9: Midterm Week10: Decision Trees Week11: Bayesian Networks Week12: Neural Networks Week13: Neural Networks Week14: Deep Learning Week15: Deep Learning Week16: Applications Week17: Project Presentations Week18: Project Presentations
30% Participation, presentation, and assignments. 20% In-class quizzes 25% Midterm 25% Term project
Artificial Intelligence: A Modern Approach, by Stuart Russell and Peter Norvig Lecture Notes