UTSA's multidisciplinary studies degree in Artificial Intelligence allows students to study multiple fields such as computer science, mathematics, statistics, electrical and computer engineering, and information systems. Artificial Intelligence is the simulation of human intelligence processes by computer systems which includes machine learning, reasoning, and self-correction. Companies like Apple, Amazon, Tesla, Netflix, Google, and others use artificial intelligence for speech recognition, voice-powered personal assistants, self-driving vehicles, and robotics.
Students seeking a B.A. degree in the Artificial Intelligence path of Multidisciplinary Studies must fulfill the university core curriculum requirements.
Students seeking a B.A. degree in the Artificial Intelligence path of Multidisciplinary Studies must fulfill the following 78 semester credit hours.
- Technology Requirement: CS 1063, CS 1083, CS 1173, DS 4003, DS 4013, IS 1413, IS 1053 (3 semester credit hours)
- Communication Requirement: COM 1043, COM 1053, COM 2113, COM 2343, COM 2733 or ENG 2413 (3hrs)
All candidates for this degree must complete three areas of focus. Courses selected to satisfy each area must be approved by the Multidisciplinary Studies Program Coordinator and the Dean of Undergraduate Studies. Furthermore, the courses used to satisfy each focus area must be completed with at least a 2.0 grade point average.
All candidates for this degree must complete MDS 2013: Introduction to Multidisciplinary Studies.
All candidates for this degree must complete MDS 4983: Senior Seminar for Multidisciplinary Studies.
All candidates for this degree must complete 27 semester hours of free electives, at least 15 of which must be at the upper-division level.
BS MDST - Artificial Intelligence 2024-26 Catalog (BS-MDAI-UC)
| FALL | SPRING | |||||
|---|---|---|---|---|---|---|
| AIS 1203 or 1223 | Academic Introduction & Strategies | 3 | CS 1714 | CS 1714 Computer Programming II (FA 2) | 4 | |
| CS 1063 | Intro to Computer Programming I | 3 | MAT 1224 | Calculus II (FA 1) | 4 | |
| MAT 1214 | Calculus I (FA 1) | 4 | STA 3003 | Applied Statistics (FA 1) | 3 | |
| CORE | Creative Arts | 3 | WRC 1023 | Freshman Comp II (Q) | 3 | |
| WRC 1013 | Freshman Comp I (Q) | 3 | ||||
| TOTAL | 16 | TOTAL | 14 | |||
| FALL | SPRING | |||||
|---|---|---|---|---|---|---|
| CS 2124 | Data Structures/Rec. (FA 2) | 4 | CS 2233 | Discrete Math (FA 1) | 3 | |
| MAT 2233 or EGR 2323 | Linear Algebra (FA 1)/Engineering Analysis (FA 1) | 3 | CS 3424 | Systems Prog/Rec (FA 2) | 4 | |
| STA 3513 | Probability and Statistics (FA 1) | 3 | CORE | Component Area Option | 3 | |
| MDS 2023 | Intro to Multidisc Studies | 3 | POL 1013 | Introduction to American Politics | 3 | |
| POL 1133 or 1213 | Texas Politics and Society | 3 | ||||
| TOTAL | 16 | TOTAL | 13 | |||
| FALL | SPRING | |||||
|---|---|---|---|---|---|---|
| CS 3343 | Analysis of Algorithms (FA2) | 3 | ELEC | Programming, Data Structure... (FA 2) | 3 | |
| STA 3523 | Mathematical Statistics (FA 1) | 3 | ELEC | Free Elective | 3 | |
| ELEC | AI & Application (FA 3) | 3 | ELEC | AI & Application (FA 3) | 3 | |
| COM 1043, 1053, 2113, 2343, 2733, ENG 2413 | Communication Requirement | 3 | ELEC | AI & Application (FA 3) | 3 | |
| CORE | Life & Physical Sciences | 3 | CORE | Life & Physical Sciences | 3 | |
| TOTAL | 15 | TOTAL | 15 | |||
| FALL | SPRING | |||||
|---|---|---|---|---|---|---|
| ELEC | Free Elective | 4 | ELEC | AI & Application (FA 3) | 3 | |
| ELEC | AI & Application (FA 3) | 3 | ELEC | Free Elective | 3 | |
| ELEC | AI & Application (FA 3) | 3 | MDS 4983 | Seminar for Multidisc Studies | 3 | |
| CORE | Social & Behavioral Sciences | 3 | CORE | Lang, Philosophy, & Cult. | 3 | |
| CORE | American History | 3 | CORE | American History | 3 | |
| TOTAL | 16 | TOTAL | 15 | |||
Focus Areas
Focus Area 1 - 18 hours prescribed (14 hours required)
| Course Number | Title | Prerequisite |
|---|---|---|
| MAT 1213 | Calculus I (required) | MAT 1093 |
| MAT 1223 | Calculus II (required) | MAT 1213 or MAT 1193 |
| MAT 2233 | Linear Algebra (required) | MAT 1223 or EGR 1333 |
| EGR 2323 | Engineering Analysis | MAT 1223 and EGR 1333 |
| CS 2233 | Discrete Mathematical Structures | MAT 1093 and CS 1083 |
| STA 3003 | Applied Statistics (required) | MAT 1093 |
| DS 3023 | Statistical Analysis for Data Science | MAT 1073 |
| STA 3513 | Probability and Statistics | STA 3003 and MAT 1224 |
| STA 3523 | Mathematical Statistics | STA 3513 |
| CE 3173 | Numerical Methods | EGR 2323 and EGR 2323 |
| EE 3423 | Mathematics in Signals and Systems | EE 2423 |
| EE 3533 | Probability and Stochastic Processes | EE 3423 |
| MAT 4113 | Computer Mathematical Topics | MAT 1214 |
| ME 3173 | Numerical Methods | EGR 3426 |
Focus Area 2 - 15 hours prescribed (9 hours required)
| Course Number | Title | Prerequisite (C- or better) |
|---|---|---|
| CS 2113 | Fundamentals of Object-Oriented Programming (required) | CS 1083 |
| CS 2123 | Data Structures (required) | CS 2113 |
| CS 3343 | Design and Analysis of Algorithms (required) | CS 2123, CS 2233, CS 3333 |
| CS 2713 | Computer Programming in C | CS 2113 |
| CS 3424 | Systems Programming | CS 2123 and CS 2713 |
| CS 3443 | Application Programming | CS 2123 |
| CS 3743 | Database Systems | CS 2123 and CS 2233 |
| CS 3843 | Computer Organization | CS 2713 |
| CS 3333 | Mathematical Foundations of Computer Science | CS 2233 and MAT 1213 |
| EE 2513 | Logic Design | EE 1322 and completion of or concurrent enrollment in CS 2073 or CPE 2073 |
| EE 2583 | Microcomputer Systems I | EE 2513 and CS 2073 or CPE 2073 |
| EE 3223 | C++ and Data Structures | EE 2583 or EE 3463 |
| EE 3563 | Digital System Design | EE 2511 and EE 2513 |
| EE 3233 | Systems Programming for Engineers | EE 3223 |
| EE 4243 | Computer Organization and Architecture | EE 2583 or EE 3463 |
| IS 2053 (IS 2043) | Programming I |
Focus Area 3 - 15 hours (9 hours from one mini track)
| Course Number | Title | Prerequisite (C- or better) |
|---|---|---|
| Data Science | ||
| DS 3023 | Statistical Analysis for Data Science | MAT 1073 |
| DS 4003 | Introduction to Data Science | MAT 1073 |
| DS 4013 | Programming for Data Science | MAT 1073 |
| DS 4023 | Data Organization and Visualization | DS 4013 and DS 3023 (or STA 3003) |
| DS 4033 | Data Mining and Machine Learning | DS 4023 |
| Statistics & Data Science | ||
| STA 3333 | Introduction to Data Science and Analysis | STA 1053 |
| STA 4133 | Intro to Prog & Data Manage SAS | |
| STA 4233 | Intro to Prog & Data Manage R | |
| STA 4643 | Introduction to Stochastic Processes | MAT 2233 and STA 3513 |
| STA 4713 | Applied Regression Analysis | Completion of or concurrent enrollment in STA 3523, or consent from instructor |
| STA 4723 | Introduction to the Design of Experiments | STA 3513 |
| STA 4753 | Time-Series Analysis | STA 3003 and STA 3513 |
| AI & Computer Science | ||
| CS 3443 | Application Programming | CS 2123 |
| CS 3743 | Database Systems | CS 2123 and CS 2233 |
| CS 3753 | Data Science | CS 2123 and CS 3333 |
| CS 3793 | Artificial Intelligence | CS 3753 and MAT 2253 |
| CS 4223 | Bioinformatics I: Algorithms for Biological Data | CS 3343 |
| CS 4233 | Bioinformatics II: Statistical Learning for Biological Data | CS 3753 or CS 4223 |
| CS 4243 | Large Scale Data Management | CS 3423 |
| CS 4373 | Data Mining | CS 3343 and 3753 |
| CS 4413 | Web Technologies | CS 3423 and 3743 |
| CS 4593 | Topics in Computer Science | Consent of Instructor |
| CS 4843 | Cloud Computing | CS 3424 |
| CS 4973 | Advanced Topics in Systems and Clouds | Consent of Instructor |
| Cyber Analytics | ||
| IS 2053 | Programming I | IS 1403 or IS 1413 |
| IS 3063 | Database Management for Information Systems | IS 2053 |
| IS 4023 | Applied Big Data with Machine Learning | IS 2053 |
| IS 4443 | Cyber Analytics I | IS 4023 and IS 3523 |
| IS 4503 | Cyber Analytics II | IS 4443 |
| IS 4463 | Web Application Security | IS 3513 with a grade of C- |
| IS 4463 | Web Application Security | IS 2063 |
| IS 4483 | Digital Forensic Analysis I | JR standing and 9 hrs of UD IS or CS coursework |
| IS 4523 | Digital Forensic Analysis II | IS 4483 |
| IS 4183 | Advanced Database Concepts and Applications | IS 3063 |
| AI & Robotics | ||
| EE 3413 | Analysis and Design of Control Systems | EE 3423 & EGR 2513 and EE 2213 |
| EE 4463 | Introduction to Machine Learning | EE 3533 |
| EE 4723 | Intelligent Robotics | EE 3413 |
| EE 4733 | Intelligent Control | EE 3413 |
| EE 4953 | Special Studies in Electrical and Computer Engineering | Consent of Instructor |
| ME 4773 | Robotics | EGR 2513 & ME 2173 |
| Neuroscience | ||
| BIO 1173 | Introduction to Computational Biology | MAT 1023 |
| BIO 1203 | Biosciences I for Science Majors | completion or conc. STA 1053, MAT 1023, MAT 1073 |
| BIO 1223 | Biosciences I for Science Majors | BIO 1203 (former BIO 1404) |
| NDRB 3433 (BIO 3133) | Neurobiology | NDRB 2113 |
| BIO 3523 | Advanced Computational Biology | BIO 1173 or CS 1173 |
| NDRB 3613 (BIO 4813) | Brain and Behavior | NDRB 2113 |
| NDRB 4823 | Cognitive Neuroscience | NDRB 2113 or PSY 4183 or consent of instructor |
| NDRB 2113 | Introduction to Neuroscience | BIO 1203 (former BIO 1404) |
| NDRB 4683 | Neural Data Science | STA 1403, CS, 1063 and NDRB 3433 or consent of instructor |
| NDRB 4783 | Computational Neuroscience | NDRB 2113 or PSY 4183 or consent of instructor |
Archived Focus Areas by Year
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Contact the Multidisciplinary Studies Program
