Artificial Intelligence

This course will be delivered in Canvas.

The Introduction to Artificial Intelligence course teaches students important programming concepts that enable the use of Artificial Intelligence in computer science and society at large. Students will learn how to incorporate basic Artificial Intelligence algorithms in their own work, and consider the social and ethical implications of how Artificial Intelligence is used, and how it plans to be used. Students will develop a series of projects that illustrate the variety of ways Artificial Intelligence can be used to optimize and predict information and processes.

There are 4 Units in this quarter class:

1. What is Artificial Intelligence? 
   Students will learn what defines Artificial Intelligence, how it is used, how it plans to be used, and the social and ethical implications of its use in society. Students will develop a case study exploring an ethical issue in Artificial Intelligence, highlighting the competing arguments on both sides of the issue, and ultimately choosing a side in the debate. 
   
   
2. Artificial Intelligence in Gaming 
   Students learn how to create interactive computer programs, where a computer "player" responds to the actions
   of a user. In the first few lessons, students build a playable game of Tic Tac Toe. Students are then introduced to
   the AI recursive function minimax that allows for game logic, and how AI in gaming should mirror human
   processing, instead of always optimizing their possible moves.
    
3. AI and Chatbots
   Students learn how chatbots are developed to interact with humans, and what forms of Artificial Intelligence are used to get them to operate. Students will create a chatbot of their own to aid a business or app to finish the unit. 
   
   
4. Creating Predictive Models 
   Students will learn how to make predictive models using linear and logistic regression. Students will explore correlation and causation, and determine if certain attributes are correlated to a specific outcome. Students will then create their own predictive models using complex data sets.