The 7 Best AI Masters Degree Programs in Texas

AI masters programs in Texas are experiencing remarkable growth. Enrollment has surged over 18% since 2024 because the industry just needs more professionals. The U.S. Bureau of Labor Statistics projects 26% growth for computer and information research scientists by 2032. This makes now the perfect time to advance your career. Graduates from artificial intelligence Texas programs report starting salaries averaging $95,000, and this reflects the state’s tech ecosystem. You’ll find excellent options that combine state-of-the-art curricula with access to tech giants like Dell and Apple. University of Texas AI specializations and programs at other institutions offer these opportunities. This list explores the seven best programs to launch your AI career.

1. University of Texas at Austin – MS in Computer Science (AI Specialization)

UT Austin leads in available AI education and offers two distinct pathways for aspiring artificial intelligence professionals through its Computer and Data Science Online (CDSO) division. You can pursue the dedicated MS in Artificial Intelligence or the MS in Computer Science with Machine Learning and AI concentration. Both programs deliver rigorous training from tenured faculty at one of the nation’s premier research universities.

Program Overview

The university launched its online Master of Science in Artificial Intelligence in partnership with edX and created one of the first online AI master’s programs from a top-tier institution. This dedicated MSAI program complements the MS in Computer Science, which offers a specialized Machine Learning and Artificial Intelligence concentration for students seeking broader computer science foundations alongside AI expertise.

Both programs share a distinctive feature: your diploma never indicates “online” completion. The degrees read as Master of Science in Computer Science or Master of Science in Artificial Intelligence and carry the same weight as on-campus credentials. All courses come from UT faculty, not adjuncts, and mirror the renowned on-campus curricula.

The flexible structure accommodates working professionals. You can enroll in one to five courses per semester and complete your degree anywhere from 18 to 36 months. Lectures are pre-recorded, so you watch them on your own schedule within each week’s prescribed timeline. Interaction with instructors and teaching assistants happens through email, Canvas, Zoom, Ed Discussion, and Slack.

Admission Requirements

You need a bachelor’s degree from a regionally accredited U.S. institution or comparable foreign degree, plus a cumulative GPA of 3.0 or higher. The admissions committee prefers applicants with degrees in artificial intelligence, computer science, electrical engineering, computer engineering, or mathematics. But they think over non-technical backgrounds case-by-case if you demonstrate relevant content knowledge through coursework or work experience.

The application requires a two-page statement of purpose describing your preparation, academic interests, professional goals, and reasons to pursue graduate study. Your CV or resume must outline educational history, work experience, publications, research, and patents. At the end, include a brief description of how you meet prerequisite courses with course titles and grades.

Letters of recommendation are optional but accepted (maximum three). The GRE is also optional for MSAI applicants. International students must submit official TOEFL or IELTS scores sent to UT Austin.

Application deadlines follow a structured timeline. Applications open December 15 for fall admission, with a priority deadline of March 15 and final deadline of April 15. Spring applications open June 1, with priority deadline August 1 and final deadline September 1. Decisions release from late January to mid-July for fall applicants and late July to mid-December for spring applicants.

Core Curriculum and AI Specializations

The MSAI program requires 30 credit hours across 10 courses. Students must complete nine hours of required foundational courses and 21 hours of electives, with one foundational course being the Ethics in AI course that addresses responsible innovation.

The MS in Computer Science with AI concentration requires one course from Theory, Systems, and Applications categories to fulfill three required courses, then you select electives aligned with your interests. To earn the Machine Learning and Artificial Intelligence concentration, complete CS 343(H) Artificial Intelligence (Honors) or CS 363D (378H) Introduction to Data Mining (Honors).

You must also take three electives from options that include CS 342 Neural Networks, CS 376 Computer Vision, CS 378 Natural Language Processing, CS 344M Autonomous Multiagent Systems, CS 344R Robotics, or CS 371R Information Retrieval and Web Search. This concentration prepares you for careers in data mining, robotics, natural language processing, and computer vision.

Tuition and Program Duration

The total tuition for both MSAI and MSCS programs costs $10,000, whatever your residency status. This breaks down to $1,000 per course or $333 per credit hour. The low-cost model makes quality education available without sacrificing academic rigor.

You must earn a B- or better in foundational/required courses and C or better in electives and maintain a minimum cumulative GPA of 3.00. The 30-credit-hour program takes between 18 and 36 months to complete, depending on your course load each semester.

Career Outcomes and Placement

Placement data for the MSAI program remains limited since its recent launch, but related UT Austin technology programs demonstrate strong outcomes. The McCombs School MS in Information Technology and Management program, which has AI and machine learning training, reports an average starting salary of $110,360 for the Class of 2025.

Graduates from this related program secured positions at Deloitte, Amazon, Oracle, Capital One, Visa, Ernst & Young, and Goldman Sachs. Job titles include AI/ML Engineer, Cloud Engineer, Software Engineer, Data Analyst, Technical Product Manager, and IT Consultant, with specialized roles such as AI Forward Deployed Engineer and Senior Consultant for AI and ML Engineering.

The MSCS program offers teaching and research positions for some students, plus summer internships through Friends of Computer Science (FoCS) partners. These internships provide hands-on experience and industry connections and help offset costs.

2. Texas A&M University – MS in Artificial Intelligence

Texas A&M University delivers its MS in Artificial Intelligence through both traditional on-campus instruction and online formats. You get flexibility to choose the learning environment that matches your professional circumstances. The Department of Computer Science and Engineering designed this STEM-designated program to build advanced skills in machine learning, natural language processing, computer vision, robotics, and AI ethics in a variety of industry applications.

Program Overview

You can pursue either a thesis or non-thesis track depending on your career objectives. The thesis option prepares you for research-intensive roles or doctoral studies through original investigation under faculty guidance. The non-thesis track focuses on coursework alone and positions you for immediate industry application. Both paths require 30 credit hours, but the thesis track dedicates 3-6 hours to research while the non-thesis track allocates those credits to additional coursework.

The online program operates with the same academic rigor as the on-campus version but delivers lectures remotely through Texas A&M’s distance education platform. Online students complete the same 30 credit hours over 1.5 to 2.5 years, depending on course load each semester. Applications open for fall or spring semester starts. Summer intake is not available currently.

Faculty connections extend beyond campus. The university maintains relationships with industry leaders and provides access to state-of-the-art research facilities. The Aggie network supports professional development throughout your career and creates opportunities for collaboration and advancement after graduation.

Admission Requirements

You need a bachelor’s degree with a minimum cumulative GPA of 3.0 on a 4.0 scale to qualify for admission. The program accepts students from various academic backgrounds. Degrees in computer science, computer engineering, data engineering, or computational fields provide the strongest preparation.

International applicants must demonstrate English proficiency through IELTS or TOEFL scores. The application requires a statement of purpose that explains your reasons for graduate study, academic interests, professional goals, and relevant preparation. Your CV or resume should detail work history, educational background, publications, research experience, and relevant coursework with associated grades.

You must provide contact information for three recommenders who can speak to your academic abilities and professional potential. The admissions committee reviews applications through GraduateCAS, where you create an account and submit all required documents. Two prerequisite courses are mandatory for thesis-track students: CSCE 411 (Analysis of Algorithms) or equivalent, plus one statistics course from STAT 436, STAT 438, STAT 601, STAT 608, or STAT 638. Take them during your first semester if you lack these courses and apply the credits toward elective hours.

Core Curriculum and AI Specializations

The curriculum splits into core courses, prescribed electives, and general electives. You must complete CSCE 625 (Artificial Intelligence) and CSCE 633 (Machine Learning) as foundational courses and earn grades of B or better in each. These six credit hours establish your theoretical base before you advance to specialized topics.

Prescribed electives require 15 hours (five courses) for non-thesis students or 9 hours (three courses) for thesis students from options including CSCE 636 (Deep Learning), CSCE 630 (Speech Processing), CSCE 631 (Intelligent Agents), CSCE 635 (AI Robotics), CSCE 638 (Natural Language Processing), CSCE 642 (Deep Reinforcement Learning), CSCE 666 (Pattern Analysis), CSCE 676 (Data Mining and Analysis), CSCE 752 (Robotics and Spatial Intelligence), and CSCE 753 (Computer Vision and Robot Perception).

The remaining credits come from graduate-level electives numbered 600 or higher that support your AI focus through related technical topics or application domains. Thesis students dedicate 3-6 credit hours to CSCE 691 (Research) under their advisory committee’s supervision. Your committee consists of at least three graduate faculty members, with your chair from the Computer Science department and at least one member from an external department.

Tuition and Program Duration

Total tuition costs $18,856 for the complete program. The 30-credit structure allows completion in 1.5 to 2.5 years based on your semester course load. Part-time students extend toward the longer timeline while maintaining employment. Full-time students finish closer to 18 months.

You must maintain a minimum 3.0 cumulative GPA throughout the program and earn B or better in core courses and C or better in electives. The thesis option adds time for research design, data collection, analysis, and manuscript preparation under your committee’s oversight.

Career Outcomes and Placement

AI master’s graduates secure full-time, AI-relevant employment at rates between 70% and 85% within the first year after completion. These figures depend on internship experience, technical specialization, employer demand patterns, and geographic location.

Graduates concentrating in natural language processing experience faster employment due to strong industry demand, though this specialization may limit flexibility for long-term career adaptability. Employer perception favors candidates with internship or practicum experience, as practical skills accelerate hiring timelines and enhance job stability in competitive sectors.

Geographic factors play a substantial role in placement outcomes. Urban tech hubs provide quicker access to positions but create tradeoffs through higher living costs and increased competition. Students should assess salary offers alongside regional cost of living, debt obligations, and advancement potential rather than focusing on nominal compensation figures alone.

3. Rice University – Master of Computer Science (AI Concentration)

Rice University’s Master of Computer Science program combines elite private education with practical career preparation, ranked #3 nationally for its online format by U.S. News & World Report. The program sits in Houston’s thriving energy and technology corridor and offers both in-person and online pathways with similar academic rigor. Your diploma shows no difference between delivery methods.

Program Overview

The MCS degree operates as a non-thesis terminal degree for students pursuing technical careers in the computer industry. You’ll complete the program in three semesters typically, though the structure accommodates both full-time and part-time enrollment. Full-time status requires enrollment in nine or more credit hours during at least one fall or spring semester at Rice.

The online version delivers the same curriculum taught by tenured Rice faculty rather than adjuncts and maintains standards similar to on-campus instruction. Pre-recorded lectures allow you to study on your schedule within weekly deadlines. Interaction occurs through Canvas, Zoom, Ed Discussion, and Slack platforms.

A distinctive feature sets Rice apart: COMP 608, the required workplace communications course. This course develops skills for explaining technical reasoning, defending decisions, and communicating clearly with teams, clients, and interviewers. It addresses the problem-solving communication gap that technical roles need beyond coding ability.

Admission Requirements

You need a bachelor’s degree in science or engineering. The admissions committee evaluates non-technical backgrounds individually if you demonstrate relevant knowledge through coursework or work experience. The ideal applicant maintains at least a 3.0 GPA in undergraduate work.

Programming prerequisites include comfort writing short programs in conventional languages (Python, Java, C, C++) and experience with statically typed languages. You should understand elementary data structures (arrays, stacks, queues, trees, graphs) and be familiar with algorithms like binary search and merge sort. Calculus-level mathematics is also required.

The GRE is optional for applicants with 3.0+ GPA. Students below 2.9 GPA should submit GRE scores, relevant work experience documentation, or strong recommendation letters. International students whose native language isn’t English must provide TOEFL scores (minimum 90 iBT or 600 paper-based) or IELTS scores (minimum 7).

Your application requires a statement of purpose that summarizes academic and professional experience, motivation for pursuing the degree, interest in computer science fields, and career application plans. Include two recommendation letters from direct supervisors, professors, or research advisors familiar with your relevant experience. The application fee costs $85.

Core Curriculum and AI Specializations

The program requires 30 semester credit hours with a minimum 2.67 cumulative GPA. You must maintain 2.67 or higher in all Rice coursework that satisfies degree requirements. Students can transfer up to six credit hours from another university with graduate committee approval, provided courses weren’t counted toward another degree.

The Artificial Intelligence specialization needs 9-12 credit hours from courses including COMP 557/ELEC 557 (Artificial Intelligence), COMP 546/ELEC 546 (Introduction to Computer Vision), COMP 550/ELEC 550/MECH 550 (Algorithmic Robotics), COMP 552 (Reinforcement Learning), COMP 646 (Deep Learning for Vision and Language), COMP 565 (Introduction to Human-Machine Interaction), and STAT 525 (Bayesian Statistics).

You also complete a 10-week to 6-month internship. You’re responsible for getting and selecting an internship that aligns with your career goals.

Tuition and Program Duration

Online MCS tuition costs $1,667 per credit hour for the 2027 academic year. Standard in-person MCS charges $3,471 per credit.

Part-time students typically complete the online program in 2-3.5 years taking one or two courses per term. Full-time students finish in 18-24 months. No financial aid is available from the university or department for MCS students.

Career Outcomes and Placement

Computer scientists earn a median salary of $131,490 according to the Bureau of Labor Statistics. Rice MCS graduates secure positions at Amazon, JP Morgan Chase, Microsoft, IBM, Chevron, and Liongard. The Class of 2025 moved into technology, finance, healthcare, energy, consulting, and research sectors.

Top metro areas for Rice master’s graduates include Houston, Dallas-Fort Worth, San Francisco, New York City, Austin, Los Angeles, and Seattle. Median starting compensation for related programs ranges from $100,000 to $160,000 in major metros. Payback timelines run 2-5 years for self-funded students entering major tech firms.

4. UT San Antonio – MS in Artificial Intelligence

UT San Antonio’s MS in Artificial Intelligence operates as an interdisciplinary program that draws courses from Computer Science, Electrical and Computer Engineering, and Management Science & Statistics departments. The program stands out among artificial intelligence Texas offerings through its groundbreaking MD/MSAI dual degree, the first of its kind nationally, which integrates medical education with AI training for students pursuing healthcare innovation careers.

Program Overview

You can select from three distinct concentrations: Analytics, Computer Science, or Intelligent and Autonomous Systems. Each concentration provides 15 credit hours of specialized coursework tailored to specific AI subfields and prepares you for industry-readiness in a variety of applications. The program requires 30 total semester credit hours and offers both thesis and non-thesis options.

The thesis track suits students interested in research or doctoral studies and dedicates six credit hours to original investigation under faculty supervision. The non-thesis option emphasizes ground applications through six additional elective courses. Both pathways begin with nine credit hours of core courses that establish AI foundations.

The MD/MSAI dual degree follows a unique timeline. You spend three years on medical studies, dedicate your fourth academic year to developing AI expertise, then complete a fifth-year capstone project that leverages clinical data with mentorship from both disciplines. You must be in your third year at UT Health San Antonio Health Science Center Long School of Medicine when applying.

Admission Requirements

You need a bachelor’s degree from an accredited institution with a minimum 3.0 GPA. Departments may review your last 60 semester credit hours. International students must score 79 on TOEFL iBT, 6.5 on IELTS, or 100 on Duolingo. Exams taken after January 21, 2026, require a minimum 4.0 iBT score on TOEFL.

Your application requires a purpose statement, current resume, and two academic or professional recommendations that demonstrate your attributes for program completion. Submit transcripts from all institutions attended; international transcripts need English translation and credential evaluation from FCSA or NACES-approved agencies. Completed applications receive decisions within 4 to 6 weeks on a rolling basis.

Core Curriculum and AI Specializations

All students complete CS 5233 (Artificial Intelligence), EE 5263 (Advanced Topics in Signal Processing and Machine Learning), and STA 5093 (Introduction to Statistical Inference) as required core courses. Each concentration then demands 15 credit hours in specialized areas. The Computer Science concentration gives you the AI algorithms, methods, systems, and tools for ground applications and culminates in capstone projects or thesis work.

Tuition and Program Duration

These figures cover tuition and fees only for fall and spring semesters. Additional costs include books ($1,200 full-time), housing ($8,110-$10,484), and meals ($4,168-$5,878) depending on living arrangements. Average UTSA master’s degree graduates from the last three years earn $75,018 a year, surpassing San Antonio’s $54,060 and Texas’s $57,300 averages.

Career Outcomes and Placement

Program graduates work at USAA, AMD, Microsoft, Oracle, Amazon, Samsung, NVIDIA, Qualcomm, and Intel. Some MS graduates pursue doctoral programs at UT Austin, Purdue University, MIT, Rice University, and Texas A&M. Healthcare-focused students develop clinical decision support tools, conduct medical research, advance precision medicine, analyze medical imaging, accelerate drug discovery, and pursue clinical informatics positions.

5. Texas State University – MS in Artificial Intelligence

Texas State University’s MS in Artificial Intelligence emphasizes generative AI, machine learning, neural networks, data analytics, and ethical AI applications through a curriculum that blends theoretical knowledge with hands-on technical skills. The 30-credit hour program positions graduates for roles in technology, healthcare and finance within Texas’s expanding AI ecosystem.

Program Overview

The program follows a structured 30-credit framework. It has four core courses, four AI-related electives, and two open electives from the graduate computer science curriculum. You can complete the degree in 1.5 to 2 years and accelerate your entry into AI careers. Students can access a dedicated multi-GPU server for high-performance computing tasks. They also get cloud credits for platforms like AWS, GCP, and Azure.

The curriculum balances foundational theory with practical implementation. You must pass both a programming exam and a communication exam to earn your degree. Texas State also offers an online MS in Computer Science option for working professionals who want flexibility. The program uses recorded lectures and faculty-guided projects.

Admission Requirements

You just need a bachelor’s degree from an accredited institution with a minimum 2.75 GPA overall or in your last 60 undergraduate credit hours. The application fee costs $55 for domestic students and $90 for international applicants. You’ll submit official transcripts, a resume that details work experience and achievements, three recommendation letters from individuals who can assess your graduate school readiness, and a statement that explains your motivation for pursuing the MSAI.

Texas State waives GRE and GMAT requirements and streamlines the admissions process. Applicants from non-computer science backgrounds may have to meet program prerequisites before full admission.

Core Curriculum and AI Specializations

Core courses include CS5315 (Responsible and Trustworthy AI), CS5329 (Algorithm Design and Analysis), CS5346 (Advanced Artificial Intelligence), and CS5369L (Machine Learning and Applications). AI electives span CS5325 (Reinforcement Learning), CS5342 (Robotics and Autonomous Systems), CS5361 (Generative Artificial Intelligence), CS7389H (Deep Learning), CS7389J (Advanced Natural Language Processing), CS7323 (Image Processing and Computer Vision), and CS7389F (Secure Cyber-Physical Systems).

Tuition and Program Duration

The online computer science program charges $500 per credit hour. This totals around $15,000 for 30 credits.

Career Outcomes and Placement

The U.S. Bureau of Labor Statistics projects 26% growth for AI specialists and computer research scientists through 2032. Austin, Dallas, and Houston show surging demand for AI professionals in technology, healthcare and finance industries.

6. Southern Methodist University – MS in Data Science and Engineering

SMU’s online Master of Science in Data Science delivers an interdisciplinary curriculum that positions you to pursue AI-driven careers through its Machine Learning & Artificial Intelligence specialization. The program operates online through a partnership with edX and combines courses from Dedman College, Lyle School of Engineering, and Meadows School of the Arts to develop detailed technical and communication skills.

Program Overview

The 33.5-credit program blends statistical analysis, programming, data mining, machine learning, database management, and data security within its core coursework. You’ll develop visualization techniques and stakeholder communication abilities with technical competencies. The Machine Learning specialization gives you the ability to build self-optimizing systems and deliver solutions for organizational challenges.

Three elective courses completed in your final two terms allow curriculum customization. You can pursue the formal Machine Learning specialization or select electives matching your career objectives without declaring a specialization. All students must attend at least one two-day on-campus immersion in Texas for networking, workshops, and faculty interaction.

Admission Requirements

SMU reviews applications without requiring GRE scores. You need a bachelor’s degree from a regionally accredited institution, quantitative skills shown through coursework or work experience, and basic programming knowledge in languages like Python, R, SAS, JAVA, C, or C++.

Submit one professional or academic recommendation letter, a resume highlighting technical experience, statement of purpose, official transcripts, and a $75 application fee. International students require TOEFL scores of 90+ or IELTS scores of 6.5+. Boot camp graduates may receive up to six graduate credit hours and potentially save over $10,000 in tuition.

Core Curriculum and AI Specializations

Core courses lay the groundwork in statistical methods, programming, and data management before advancing to machine learning algorithms, neural networks, and AI applications. The specialization focuses on computational algorithms that broaden machine cognitive capabilities.

Tuition and Program Duration

Tuition costs $1,130 per credit with an additional $100 distance learning fee per credit. Total program cost reaches about $37,855 without fees. Complete the degree in 18 to 36 months depending on your course load.

Career Outcomes and Placement

SMU’s related data engineering graduates achieve 100% employment within six months. They earn average starting salaries of $110,000 as of 2024.

7. University of North Texas – MS in Artificial Intelligence

UNT positions itself among Texas’s pioneering AI graduate programs and offers the state’s first dedicated Master of Science in Artificial Intelligence with three specialized concentrations. The Department of Computer Science and Engineering maintains innovative research facilities that support both theoretical and applied computer science education.

Program Overview

Students choose from Machine Learning, Biomedical Engineering, or Autonomous Systems concentrations tailored to specific career pathways. The STEM-designated program operates on-campus in Denton or online and requires 33 credit hours completed over 2-3 years. A combined B.S./M.S. track allows undergraduate students to take graduate coursework early and accelerate degree completion.

Admission Requirements

Applicants must hold a bachelor’s degree in computer science or related field with a 3.0 GPA minimum. International students must score 79 on TOEFL iBT, 6.0 on IELTS, 53 on PTE, or 100 on Duolingo. Prerequisites include courses in statistics, linear algebra, and logic.

Core Curriculum and AI Specializations

Core courses cover Introduction to Big Data and Data Science, Machine Learning, Data Mining, and AI for Wearables and Healthcare. Bridge courses include Software Development for Artificial Intelligence and Fundamentals of Artificial Intelligence for students needing foundational preparation.

Tuition and Program Duration

Texas residents pay around $18,700 in annual tuition. International students pay $16,651 per year. Teaching and research assistantships provide monthly stipends and may qualify students for in-state rates.

Career Outcomes and Placement

Graduates pursue roles as data scientists, software engineers, and machine learning engineers in technology, healthcare, and autonomous systems industries.

Next Steps

Texas offers a variety in AI master’s programs, from UT Austin’s available $10,000 option to Rice University’s elite online MCS and Texas A&M’s detailed curriculum. Each program brings different advantages: affordability, specialization depth and flexible delivery formats. Your choice depends on budget constraints, career objectives, preferred learning environment and technical background. AI roles in Texas show 26% projected growth. Starting salaries average $95,000. Investing in these programs positions you within the state’s expanding tech ecosystem. Assess program costs against career goals and review specialization options. Select the pathway that lines up with your professional aspirations.