Georgia Institute of Technology Ivan Allen College of Liberal Arts 81 courses 15 total credits
The interdisciplinary minor in Applications of Artificial Intelligence and Machine Learning will equip undergraduate students with skills and knowledge to use AI and ML to solve problems in engineering, humanities, and social sciences. The curriculum is designed to also provide students with the insight to describe and discuss current ethics and policy frameworks related to AI and machine learning. The minor is open to students pursuing majors in the Ivan Allen College of Liberal Arts, the College of Engineering, the Scheller College of Business, and the College of Sciences. For up-to-date information on which majors are eligible to participate, as well as contact info for the corresponding advisers, please see the website https://sites.gatech.edu/apps-ai-ml-minor/. The minor consists of four tracks. Any student admitted to the minor is eligible to choose either track. No βmix and matchβ is allowed between the tracks, so students are strongly encouraged to discuss with their academic advisor which track best matches their interest and career goals, and which is most compatible with major requirements. The Minor in Applications of Artificial Intelligence and Machine Learning has the following Learning Outcomes: Upon completion of this minor, all students will be able to:
| Total Credits | 15 credits |
Core Course 1 - Select one from the following:
Core Course 2 - Select one of the following:
Core Course 3
Core Courses
| Code | Course Title | Credits |
|---|---|---|
| PHIL 3101 | AI Ethics and Policy | 3 |
Select two of the following:
Research Credit (3 hours max with approval)
Core Course 1 - Select one of the following:
| Code | Course Title | Credits |
|---|---|---|
| ECON 2250 | Statistics for Economists | 3 |
| PUBP 3120 | Statistical Analysis for Public Policy | 3 |
| Total | 3 credits | |
Core Course 2 - Select one of the following:
Core Course 3
| Code | Course Title | Credits |
|---|---|---|
| ECON 4803 | Special Topics in Economics | 3 |
| PUBP 3042 | Data Science for Public Policy | 3 |
| INTA 4803 | Special Topics | 3 |
| Total | 3 credits | |
Core Courses:
| Code | Course Title | Credits |
|---|---|---|
| PHIL 3101 | AI Ethics and Policy | 3 |
Select 2 of the following:
Research Credit (3 hours max with approval)
Core Courses:
Core Course 1: Core Course 2: Core Course 3:
| Code | Course Title | Credits |
|---|---|---|
| MGT 2250 | Management Statistics | 3 |
| MGT 4803 | Special Topics in Management | 3 |
| PHIL 3101 | AI Ethics and Policy | 3 |
Elective Courses
Select 2 of the following: Research Credit XXXX 4699 (3 hours max with approval)
Core Course 1 - Select one from the following:
Core Course 2 - Select one of the following:
Core Course 3:
| Code | Course Title | Credits |
|---|---|---|
| CHEM 4414 | Introductory Data Science and Machine Learning for Science | 3 |
| MATH 4210 | Mathematical Foundations of Data Science | 3 |
| MATH 4740 | Computational Methods for Simulation and Machine Learning | 3 |
| PSYC 4803 | Special Topics | 3 |
| Total | 3 credits | |
Core Courses
| Code | Course Title | Credits |
|---|---|---|
| PHIL 3101 | AI Ethics and Policy | 3 |
Elective Courses
Select two of the following: Research Credit XXXX 4699 (3 hours max with approval)
Click a course code or title to read the full course description.
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