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)

FIRST YEAR - FALL

The table shows courses available to take the fall semester of your first year.
Course Code Course Name Credit Hours
AIS 1203 or 1243 Academic Inquiry and Scholarship 3
Computer Science requirement 1083 3
MAT 1213 Calculus I (FA 1 and CORE) 4
CORE Creative Arts 3
WRC 1013 Freshman Comp I (Q) 3
TOTAL   15

FIRST YEAR - SPRING

The table shows courses available to take the spring semester of your first year.
Course Code Course Name Credit Hours
CS 2113 Computer Programming II (FA 2) 3
MAT 1223 Calculus II (FA 1) 3
STA 3003 Applied Statistics (FA 1) 3
WRC 1023 Freshman Comp II (Q) 3
CORE American History  
TOTAL   15

SECOND YEAR - FALL

The table shows courses available to take the fall semester of your second year.
Course Code Course Name Credit Hours
CS 2123 Data Structures (FA 2) 3
MAT 2233 Linear Algebra (FA 1) 3
ELEC Focus Area 1 3
MDS 2023 Intro to Multidisc Studies 3
POL 1133 or 1213 Texas Politics and Society 3
TOTAL 15

SECOND YEAR - SPRING

The table shows courses available to take the spring semester of your second year.
Course Code Course Name Credit Hours
ELEC Focus Area 1 3
ELEC Focus Area 2 3
CORE Component Area Option 3
POL 1013 Introduction to American Politics 3
CORE American History 3
TOTAL 15

THIRD YEAR - FALL

The table shows courses available to take the fall semester of your third year.
Course Code Course Name Credit Hours
CS 3343 Design and Analysis of Algorithms (FA 2) 3
ELEC Free Elective 3
ELEC Focus Area 3 3
COM Requirement COM 1043,1053,2113, 2343,2733, ENG 2413 3
CORE Life & Physical Sciences 3
TOTAL 15

THIRD YEAR - SPRING

The table shows courses available to take the spring semester of your third year.
Course Code Course Name Credit Hours
ELEC Focus Area 2 3
ELEC Focus Area 2 3
ELEC Focus Area 3 3
ELEC Focus Area 3 3
CORE Life & Physical Sciences 3
TOTAL 15

FOURTH YEAR - FALL

The table shows courses available to take the fall semester of your fourth year.
Course Code Course Name Credit Hours
ELEC Free elective 3
ELEC Focus Area 3 3
ELEC Focus Area 3 3
CORE Social & Behavioral Sciences 3
ELEC Free elective 3
TOTAL 15

FOURTH YEAR - SPRING

The table shows courses available to take the spring semester of your fourth year.
Course Code Course Name Credit Hours
ELEC Focus Area 3 3
ELEC Free elective 3
MDS 4983 Seminar for Multidisc Studies 3
CORE Lang, Philosophy, & Cult. 3
ELEC Free elective 3
TOTAL 15

Focus Areas

Focus Area 1 - 18 hours (9 hours prescribed) 6 hrs UD (9 hours *required)

The table shows some of the courses you can take in the focus area for Mathematics & Statistics.
Course Number Title Prerequisite (C- or better)
MAT 1213* Calculus I (required) MAT 1093 or equivalent or satisfactory performance on a placement examination.
MAT 1223* Calculus II (required) MAT 1213 (or MAT 1214 in previous catalogs) or MAT 1193, or equivalent
MAT 2233 Linear Algebra MAT 1223 (or MAT 1224 in previous catalogs)
EGR 2323 Applied Engineering Analysis I Completion of MAT 1223 or EGR 1333 (or MAT 1224 or EGR 1324 in previous catalogs), or equivalent.
EGR 2313 Multivariable Calculus and Series for Engineers Completion of MAT 1223 or EGR 1333 (or MAT 1224 or EGR 1324 in previous catalogs), or equivalent.
CS 2233 Discrete Mathematical Structures MAT 1093 and one of the following: CS 1083, CS 1063, CS 2073, CPE 2073.
STA 3003* Statistical Methods & Application (required) Completion of MAT 1093 (or equivalent).
DS 3023* (Can use this or STA 3003) Statistical Analysis for Data Science (required) MAT 1073 or the equivalent
STA 3513 Probability STA 3003, MAT 1223 or STA 3023, and completion of or concurrent enrollment in MAT 2213.
STA 3523 Mathematical Statistics for Inference STA 3513 or an equivalent
CE 3173 Numerical Methods EGR 2323 or EGR 3423
EE 2423 Electric Network Theory EE 1322 and completion of or concurrent enrollment in EGR 3423 and PHY 1963
EE 3423 Mathematics in Signals and Systems EE 2423
EE 3533 Probability and Random Signals EE 3423
MAT 4113 Computer Mathematical Topics MAT 1213 (or MAT 1214 in previous catalogs)
ME 3173 Numerical Methods EGR 3423

Focus Area 2 - 15 hours (6 hours prescribed) 6 hrs UD (6 hours *required)

The table shows some of the courses you can take in the focus area for Programming, Data Structures & Algorithms.
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 CS 2123, CS 2233 and CS 3333
CS 2713 Computer Programming in C CS 2113
CS 3423 Systems Programming CS 2123 & CS 2713
CS 3443 Application Programming CS 2123
CS 3743 Database Systems CS 2123 & CS 2233
CS 3843 Computer Organization CS 2713 or equivalent.
CS 3333 Mathematical Foundations of Computer Science CS 2233 and MAT 1213 (or MAT 1214 in previous catalogs)
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 3233 Systems Programming for Engineers EE 3223
EE 3563 Digital System Design EE 2513
EE 4243 Computer Organization and Architecture EE 2583 or EE 3463
ISC 2053 Programming I ISC 1203, or equivalent, with a grade of "C-" or better.
Engineering
CE 3173 requires EGR 3423 as a prereq (not included in FA1 elective options and has prereqs of its own)
EE 3423 requires EE 2423 (included in FA1 electives already, but EE 2423 has its own prereqs not included)
EE 3533 requires EE 3423 (included in FA1 electives already)
MAT 4113 requires MAT 1213 (already required in FA1)
ME 3173 requires EGR 3423 as a prereq (not included in FA1 elective options and has prereqs of its own)
STA 3513 requires STA 3003 (already an FA1 option) and MAT 1223 (already required in FA1)
STA 3523 requires STA 3513 (included in FA1 electives already)

Focus Area 3 - 15 hours (9 hours from one mini track) 6 hrs UD

The table shows some of the courses you can take in the focus area for Artificial Intelligence and Applications.
Course Number Title Prerequisite (C- or better)
MAT 2213 Calculus III MAT 1223 (or MAT 1224 in previous catalogs) or equivalents. NOTE: This course is a hidden pre-req that needs to be coded in degree works as an option for all topical areas in Focus Area 3 of this degree track.
Data Science
DS 4003 Introduction to Data Science MAT 1073 or the equivalent; students may not enroll without 30 credit hours completed.
DS 4013 Programming for Data Science MAT 1073 or the equivalent
DS 4023 Data Organization and Visualization DS 3023, DS 4003, and DS 4013 or the equivalents
DS 4033 Data Mining and Machine Learning completion of or concurrent enrollment in DS 4023
Statistics & Data Science
STA 3333 Introducation to Data Science and Analysis One of the following: MS 1023, STA 1053, STA 1403, STA 2303, or an equivalent
STA 4133 or 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 (or equivalents)
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, or equivalents
STA 4753 Time-Series Analysis STA 3003 and STA 3513, or equivalents
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 Artifical Intelligence CS 2123, CS 3333, 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 3763 or CS 4223
CS 4243 Large Scale Data Management CS 3423
CS 4373 Data Mining CS 3343 and either CS 3753 or CS 3763
CS 4413 Web Technologies CS 3443
CS 4593 Topics in Computer Science Consent of Instructor
CS 4843 Cloud Computing CS 3423
CS 4963 Advanced Topics in Systems and Clouds Consent of Instructor
Cyber Analytics
ISC 1003 Unlocking Cyber
ISC 2053 Programming I ISC 1203, or equivalent, with a grade of "C-" or better. (They will accept DS 4013 as the pre-req.)
ISC 3063 Database Management for Information Systems
ISC 3523 Intrusion Detection and Incident Response. ISC 3033 and ISC 3513, or equivalents, with a grade of "C-" or better.
ISC 3513 Information Assurance and Security ISC 3413, or equivalent, with a grade of "C-" or better.
ISC 3413 Telecommunications and Networking ISC 1003, or equivalent, with a grade of "C-" or better.
ISC 4023 Applied Big Data with Machine Learning ISC 2053, or equivalent, with a grade of C- or better.
ISC 4443 Cyber Analytics I ISC 4023 and ISC 3523, or equivalents, with a grade of "C-"or better. (Hidden Pre-reqs IS 3513, 3413 and 1003)
ISC 4503 Cyber Analytics II ISC 4443, or equivalent, with a grade of "C-" or better.
ISC 4483 Digital Forensic Analysis I Students may not enroll without having completed 60 credit hours and without having completed nine (9) hours of upper-division ISC (formerly IS) and/or CS coursework.
AI & Robotics
EE 3413 Analysis and Design of Control Systems EE 3423 for electrical engineering majors; EGR 2513 and EE 2213 for mechanical engineering majors.
EE 4463 Introduction to Machine Learning EE 3533
EE 4723 Intelligent Robotics EE 3413 or ME 3543
EE 4733 Intelligent Control EE 3423
EE 4953 Special Studies in Electrical and Computer Engineering May vary with the topic (refer to the course syllabus on BB or contact the instructor)
ME 4773 Robotics EGR 2513; and ME 3173 (or ME 2173 in previous catalogs)
Neuroscience
BIO 1173 Introduction to Computational Biology MAT 1023
BIO 1203 Biosciences I for Science Majors Completion of or concurrent enrollment in one of the following: STA 1053, MAT 1023, MAT 1073, or higher.
BIO 1223 Biosciences II for Science Majors BIO 1203. Corequisite: BIO 1221 is required for biology majors.
BIO 3523 Advanced Computational Biology BIO 1173 or CS 1173
NDRB 3433 (BIO 3133) Molecular and Cellular Neurobiology NDRB 2113 required for Neuroscience Majors; BIO 1203 for all non-majors.
NDRB 3613 (BIO 4813) Brain and Behavior NDRB 2113
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 MAT 1193 and CS 1063 (or equivalents), and NDRB 2113, or consent of the instructor.
NDRB 4823 Cognitive Neuroscience NDRB 2113 or PSY 4183 or consent of instructor

Archived Focus Areas by Year

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