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 22-24 catalog (BS-MDAI-UC)

FALL   SPRING
AIS 1203 or 1223 Academic Inquiry and Scholarship 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 - 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

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

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

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