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.
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 | |||
2023 Focus Areas
2023 Focus Area 1 - 21 hours (14 hours required)
| Course Number | Title | Prerequisite |
|---|---|---|
| MAT 1214 | Calculus I (required) | MAT 1093 |
| MAT 1224 | Calculus II (required) | MAT 1214 |
| EGR 2233 | Linear Algebra (required) | MAT 1224 |
| EGR 2323 | Engineering Analysis | MAT 1224 |
| CS 2233 | Discrete Mathematical Structures | CS 1714 and MAT 1214 |
| STA 3003 | Applied Statistics (required) | MAT 1093, Co-requisite MAT 1214 |
| STA 3513 | Probability and Statistics | STA 3003 and MAT 1224 |
| STA 3523 | Mathematical Statistics | STA 3513 |
| CE 3173 | CE 3173 Numerical Methods | CS 1173 and EGR 2323 |
| EE 3423 | Mathematics in Signals and Systems | EE 2423 and EGR 2323 |
| EE 3533 | Probability and Stochastic Processes | EE 3423 and EGR 2323 |
| MAT 4113 | Computer Mathematical Topics | MAT 1214 |
| MR 2173 | Numerical Methods | EGR 2323 |
2023 Focus Area 2 - 18 hours (11 hours required)
| Course Number | Title | Prerequisite (C- or better) |
|---|---|---|
| CS 1714 | Computer Programming II (required) | CS 1063 or CS 1083 |
| CS 2124 | Data Structures (required) | CS 1714 and MAT 1214 |
| CS 3343 | Analysis of Algorithms (required) | CS 2124 and CS 3333 (MAT 2233 and STA 3003) |
| CS 3424 | Systems Programming | CS 2124 |
| CS 3443 | Application Programming | CS 2124 |
| STA 3743 | Database Systems | CS 2233 and CS 3424 |
| CS 3844 | Computer Organization | CS 2124 |
| EE 3463 | Microcomputer Systems I | EE 2513 and CS 2073 |
| EE 3223 | C++ and Data Structures | EE 3463 |
| EE 3233 | Systems Programming for Engineers | EE 3223 |
| EE 3563 | Digital System Design | EE 2511 and EE 2513 |
| EE 4243 | Computer Organization and Architecture | EE 3463 |
| IS 2053 (IS 2043) | Programming Languages I with Scripting | IS 1003 |
2023 Focus Area 3 - 18 hours (12 hours from one mini track)
| Course Number | Title | Prerequisite (C- or better) |
|---|---|---|
| Data Science | ||
| DS 4003 | Introducation to Data Science | MAT 1073 |
| DS 4013 | Programming for Data Science | MAT 1073 |
| DS 4023 | Data Orgranizaiton 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 or | Intro to Prog & Data Manage SAS | |
| STA 4233 | Intro to Prog & Data Manage R | |
| STA 4643 | Introduction to Stochastic Processes | STA 3513 |
| STA 4713 | Applied Regression Analysis | STA 3003 |
| STA 4723 | Introduction to the Design of Experiments | STA 3003 |
| STA 4753 | Time-Series Analysis | STA 3513 |
| AI & Computer Science | ||
| CS 3443 | Application Programming | CS 2124 |
| CS 3743 | Database Systems | CS 2124 and CS 3424 |
| CS 3753 | Data Science | CS 2124, CS 2233 and CS 3333 (need instructor consent) |
| CS 3793 | Artifical Intelligence | CS 3343 |
| CS 4223 | Bioinformatics and Big Data | CS 3343 or consent of instructor |
| CS 4233 | Computational Biology and Bioinformatics | CS 3343 |
| CS 4243 | Large Scale Data Management | CS 3423 and CS 3443 |
| CS 4373 | Data Management | CS 3343 |
| CS 4413 | Web Technologies | CS 3424 |
| 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 Languages I with Scripting | IS 1003 |
| 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 4483 | Digital Forensic Analysis I | |
| IS 4523 | Digital Forensic Analysis II | IS 4483 |
| IS 4183 | Advanced Database Concepts and Applications | IS 3063 with a grade of C- |
| AI & Robotics | ||
| EE 3413 | Analysis and Design of Control Systems | EE 3423 & EGR 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 | |
| BIO 1203 | Biosciences I for Science Majors | |
| BIO 1223 | Biosciences I for Science Majors | |
| BIO 3433 | Neurobiology | |
| BIO 3523 | Advanced Computational Biology | |
| BIO 4813 | Brain and Behavior | |
| BIO 4823 | Cognitive Neuroscience | |
| NDRB 2113 | Introduction to Neuroscience | |
| NDRB 4683 | Neural Data Science | |
| NDRB 4783 | Computational Neuroscience | |
| NDRB 4813 | Brian and Behavior | |
| NDRB 4823 | Cognitive Neuroscience | |
Want to learn more about this program?
Contact the Multidisciplinary Studies Program
