Applied Artificial Intelligence, Minor
Program Overview
The minor in applied artificial intelligence is available to all undergraduate students. No prior experience or knowledge in computing is assumed or required. Students completing the minor in applied artificial intelligence will learn how modern artificial intelligence applications work, how to choose the appropriate application for a problem, how to correctly deploy an artificial intelligence application, and how to weigh the benefits and risks of using the application. Students will gain practice in applying artificial intelligence techniques in different disciplines.
Learning Outcomes
- Students completing the program will have the ability to apply techniques and tools of artificial intelligence to solve novel problems in a discipline of their choice.
- Students completing the program will have the ability to make informed judgements about the proper artificial intelligence tools to use in different problem scenarios.
- Students completing this program will recognize their professional responsibilities and have the tools to make informed judgements about the societal benefits and risks of applications they are building.
Undergraduate Policies
For undergraduate policies and procedures, please review the Undergraduate Academics section of the General Bulletin.
Program Requirements
The minor in applied artificial intelligence consists of five courses: two required courses; one course on the societal impacts of artificial intelligence; and two electives where students apply artificial intelligence techniques in different disciplines.
| Code | Title | Credit Hours |
|---|---|---|
| Required Courses: | ||
| CSDS 101 | The Digital Revolution: Computer and Data Science For All | 4 |
| CSDS 102 | Artificial Intelligence for All Disciplines | 3 |
| Societal Impact Course | 3 | |
| Choose one of the following: | ||
| Current Issues in Artificial Intelligence, For Better or Worse | ||
| Responsible AI: Cultivating a Just and Sustainable Socio-technical Future through Data Citizenship | ||
| The Politics of Artificial Intelligence | ||
| Ethics of Artificial Intelligence and Emerging Technology | ||
| AI Application Electives | 6 | |
| Choose at least two of the following for at least six credits: | ||
| Applying Artificial Intelligence and Blockchain in Business and Finance | ||
| Financial Data Science: Data Analytics & Machine Learning Fundamentals | ||
| Financial Modeling | ||
| Corporate Risk Management | ||
| Machine Learning and Artificial Intelligence in Business Analytics | ||
| Cognition and Computation | ||
| Advanced Econometrics | ||
| Economics of Artificial Intelligence and Digital Platforms | ||
| Computational Methods for Economic Modeling | ||
| Machine Learning for Predictive Analytics in Economics | ||
| Algorithmic Trading | ||
| Coding for the Humanities: Python, Natural Language Processing, and Machine Learning | ||
| Artificial Intelligence Applications in Healthcare Management | ||
| AI in Medicine: Knowledge Representation and Deep Learning | ||
| Introduction to Data Science for Social Impact | ||
| Semester Research Project in Data Science for Social Impact | ||
| Artificial Intelligence Fundamentals for Supply Chain Management | ||
| Case Studies in Artificial Intelligence - Supply Chain Applications | ||
| Artificial Intelligence for Biomedical Research | ||
| Total Credit Hours | 16 | |