Module 1:

Logistics and introduction

TOPICS: Course logistics, introductions to each other, project introduction, intelligent agents

LENGTH: 1 Week

DATES: Aug 23-29

Module 2:

Intelligent search

TOPICS: Uninformed and informed search techniques

LENGTH: 2 weeks

DATES: Aug 29 – Sep 12

Module 3:

search in the real world

TOPICS: Local search, evolutionary computation/search, adapting search to handle real-world complexities

LENGTH: 1 week

DATES: Sep 12-19

Module 4:

Adversarial Search 

TOPICS: Search with adversaries (e.g. games)

LENGTH: 2 weeks

DATES: Sep 19 – Oct 3

Module 5:

Planning & Multi-Agent Systems

TOPICS: Knowledge representation, Planning methods to achieve goals, multiple agents

LENGTH: 2 weeks

DATES: Oct 3 – 17

Module 6:

Introduction to Machine learning

TOPICS: Machine learning overview, simple unsupervised and supervised methods include clustering, local learning, and regression

LENGTH: 1 week

DATES: Oct 17-24

Module 7: 

Decision Trees and ensemble methods

TOPICS: Decision Trees and Ensemble methods

LENGTH: 1 week

DATES: Oct 24-31

Module 8: 

Neural Networks and Deep Learning

TOPICS: Overview of neural networks and deep learning methods (note, there is a separate entire class on this topic at OU called Advanced Machine Learning so this is a brief overview)

LENGTH: 1 week

DATES: Oct 31 – Nov 7

Module 9:

Reinforcement Learning

TOPICS: Foundational RL methods including TD learning, Q-learning, and learning in the real-world

LENGTH: 1 week

DATES: Nov 7 – Nov 14

Module 10:

Ethical & responsible AL/ML

TOPICS: What can we do to ensure AI is ethical and responsibly developed and used in all applications?

LENGTH: 3 weeks

DATES: Nov 14 – Dec 10 (overlaps Thanksgiving break week so it is 4 weeks long)

Project Module

Project information 

In The News

AI in the news

Important Links

Syllabus, Class code of Conduct, Book information