|Course Dates||Length||Meeting Times||Status||Format||Instructor(s)||CRN|
|June 28, 2021 - August 11, 20216/28 - 8/11||6 Weeks||Online||Waitlisted||Online||Justin Dong|
Jeova Farias Sales Rocha Neto
One of the most influential and fastest growing fields of research is artificial intelligence. This technology has dramatically changed the job market, communication, search engines, and entertainment. The goal of this course is to take an interdisciplinary approach to introduce students to artificial intelligence. The structure of this course will be to look at how neuroscience has inspired artificial intelligence models and then translate these ideas into mathematical models that can be programmed into a computer.
As an introduction to the course, we’ll learn about the connectome project which has been ongoing project to map the structural connectivity of the neurons in the brain. This model is related to an AI model called a neural network which will be the focus of the beginning of the course. Our goal is to learn how to program a neural network that can recognize handwritten numbers. In order to accomplish this objective, we will learn basic linear algebra to construct a neural net, calculus to understand how to train a neural net which is also referred to as the learning process.
Toward the end of the course, we will focus on graphical models and a message passing algorithm called belief propagation. We will learn about networks and how they can be used to model various problems such as restoring an image and predicting traffic flow. The underlying math to these models is probability because these models make predictions by choosing the outcome that is most likely.
The primary objective of the course is to introduce high school students to artificial intelligence, which is a topic they've heard of but perhaps never formally studied. These students will leave the course with some mathematical knowledge of linear algebra, calculus, and probability. In addition, they will be introduced to two very active areas of research in artificial intelligence. Most importantly, I want the students to see that mathematics is essential to the process of developing artificial intelligence.
Prerequisites: Basic algebra. No programming experience is required.