Best Associate's Machine Learning Degree Programs in Texas
Houston Community College — Houston, TX
Key Distinction: Houston Community College provides affordable Machine Learning education with flexible scheduling and transfer pathways to four-year universities.
Hakia Insight: Houston Community College's affordability and flexible scheduling serve regional energy and petrochemical sectors where companies prefer hiring associates-degree holders willing to train on proprietary systems over four-year degree holders with Silicon Valley expectations.
Houston Community College offers Machine Learning programs in Houston, TX. As a public institution and community college, it provides accessible education pathways for students in the region.
El Paso Community College — El Paso, TX
Key Distinction: El Paso Community College's technology programs focus on hands-on manufacturing and machining skills rather than computer science or machine learning applications.
Hakia Insight: El Paso Community College's machining-focused technical programs reveal a regional economy diverging from pure software ML—the distinction matters for students in manufacturing-heavy labor markets where embedded systems and industrial automation ML commands different skill sets.
At the associate's level, based on the available information, El Paso Community College does not appear to offer a dedicated Machine Learning program. The source pages primarily detail a Machining Technology program at the Advanced Technology Center, which focuses on precision manufacturing techniques, CNC operations, and programming. This program teaches students to use milling machines, lathes, grinders, and Computer Numerical Control (CNC) systems to create metal parts. The curriculum includes engineering drawing, 3D printing, metrology, basic lathe and mill operations, surface grinding, CNC programming, electrical discharge machines (EDM), and introduction to CAD/CAM software. The program prepares students for high-paying jobs in the metal trades industry and global manufacturing economy. While this is a technology-focused program, it is mechanical/manufacturing technology rather than machine learning or artificial intelligence.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Top Transfer Destinations
- University of Texas at El Paso
- New Mexico State University
- Texas Tech University
Entry-Level Career Paths
- Data Technician
- Analytics Support Specialist
- Junior Data Analyst
- Database Support Associate
Included Certifications
- Microsoft Azure Data Fundamentals
- Google Cloud Associate Cloud Engineer
- CompTIA Data+ (CompTIA Data Analytics)
Location Advantages:
South Texas College — McAllen, TX
Key Distinction: STC is a designated AWS-Member institution that embeds Amazon Web Services Machine Learning curriculum directly into bachelor's degree coursework, providing students with industry-recognized AWS certifications alongside their degree.
Hakia Insight: South Texas College's AWS-Member status embedding Amazon's ML curriculum directly into degree coursework means students graduate with industry certifications before they finish their associates—eliminating the typical two-step of degree-then-cert that delays hiring timelines.
At the associate's level, south Texas College's Machine Learning program is integrated into their Bachelor of Applied Technology in Computer and Information Technologies (BAT-CIT) degree, launched in fall 2023. The program incorporates AWS Academy Machine Learning Foundations curriculum into existing coursework, providing hands-on experience with Python programming, algorithms, and statistics for applications in image recognition, fraud detection, and product recommendations. Students earn AWS certificates in Machine Learning and Natural Language Processing while completing courses like CITP 3304 Fundamentals of Python and Machine Learning, CITP 3309 Machine Learning for Natural Language Processing, and CITP 4349 Advanced Artificial Intelligence. The program balances theoretical knowledge with practical skills, preparing students for careers in healthcare, financial sectors, and transportation through partnerships with Amazon Web Services and Google IT Automation certifications.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Industry Partners
- Amazon Web Services (corporate)
- Google (corporate)
- The Coding School (nonprofit)
Notable Faculty
- Dr. Meng-Hung Wu — Machine Learning and AWS Academy curriculum
- Nicholas Hinojosa — Computer Information Technology and Artificial Intelligence
- Nicolas Gutierrez — Computer Information Technology
Accreditations and Certifications
- AWS Certificate in Machine Learning
- AWS Certificate in Natural Language Processing
- Google IT Automation with Python
- AWS Academy Machine Learning Foundations
Location Advantages: AWS-Member institution status providing direct access to Amazon curriculumPartnership with international nonprofit organizations for professional development
Lone Star College System — The Woodlands, TX
Hakia Insight: Lone Star's Energy & Manufacturing Institute and state-of-the-art Learning Innovation Lab position students for Texas's oil, gas, and refining sectors where ML for predictive maintenance and process optimization is a decade ahead of fashion-industry hype cycles.
At the associate's level, lone Star College System offers an Artificial Intelligence and Machine Learning Program as part of their 200+ degree and certification programs.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Location Advantages: Access to Energy & Manufacturing Institute with state-of-the-art facilitiesLearning Innovation Lab with cutting-edge equipment including 3D printers, VR headsets, and electronics labCareer Star job placement website specifically focused on degree programs
Collin County Community College District — McKinney, TX
Hakia Insight: Collin College's continuing education model in data science and AI suggests a pragmatic regional approach—short certifications rather than full degrees may better match job openings in DFW's rapidly evolving tech hiring patterns where six-month bootcamp graduates compete with degree holders.
At the associate's level, collin College offers continuing education courses in data science, artificial intelligence, and machine learning rather than a formal degree program. The Data Science Certificate Series includes three courses covering data life cycle, analytics, programming, and visualization skills, while AI courses explore machine learning applications and large language models.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Odessa College — Odessa, TX
Hakia Insight: Odessa College's partnerships with Chevron and Halliburton mean students aren't learning ML theory in a vacuum—they're solving actual production optimization and predictive maintenance problems that directly transfer to entry-level roles in the energy sector.
At the associate's level, machine learning isn't abstract at Odessa College—it solves real problems in West Texas oil and gas, healthcare, and logistics industries. The program emphasizes practical data analysis, predictive modeling, and working with messy real-world datasets, so you graduate knowing how to deliver value immediately. Instructors bring industry experience to the classroom, and the tight-knit college community means networking opportunities with regional employers who actively recruit from OC. Graduates transfer to UT Permian Basin or University of Texas at El Paso, or launch directly into data technician and analyst positions.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Industry Partners
- Chevron (energy)
- Halliburton (oil services)
Career Outcomes
Median Salary: $35,000. Top Employers: Local IT companies, Energy sector, Government agencies.
Admissions
GPA Requirement: 2.0.
Accreditations and Certifications
- CompTIA A+
- Microsoft Office Specialist
Top Transfer Destinations
- University of Texas of the Permian Basin
- University of Texas at El Paso
- Texas Tech University
- Angelo State University
Entry-Level Career Paths
- Data Analyst
- Junior Data Technician
- Analytics Support Specialist
- Database Technician
Included Certifications
- AWS Cloud Practitioner
- Microsoft Azure Fundamentals
- CompTIA Data+ (CompTIA Data Analytics)
Dallas College — Dallas, TX
Key Distinction: Dallas College's BAT in Software Development offers bachelor's degree education at community college prices ($99 per credit hour for in-county residents) with both fully online and in-person delivery options, making advanced software development education highly accessible.
Hakia Insight: Dallas College's $99/credit-hour BAT in Software Development undercuts traditional community colleges while offering the same machine learning coursework, creating an unusual arbitrage for in-county residents seeking a bachelor's-level credential at associate's pricing.
At the associate's level, dallas College offers a Bachelor of Applied Technology (BAT) in Software Development through their School of Engineering, Technology, Mathematics and Sciences. This innovative program provides students with community college pricing for a bachelor's degree in the high-demand field of software development. The program features flexible scheduling with both in-person classes at the Richland Campus and 100% online options. Students benefit from stackable credentials, dedicated BAT faculty specializing in the field, and coding-oriented classes with lab components to develop industry-required skills. The program prepares graduates to work directly in the Software Development industry with hands-on experience and practical knowledge. Upper-level courses include specialized machine learning components with courses like ITAI 4301 Principles in Machine Learning and ITAI 4350 Projects in Machine Learning, demonstrating the program's comprehensive approach to modern software development including AI technologies.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Notable Faculty
- Daniel, Midhun — Machine Learning
- Pierce, Russell — Machine Learning Projects
Location Advantages: Multiple campus locations across Dallas areaRichland Campus with 50 years of experienceSTEM Center availableWinner of Malcolm Baldrige National Quality Award
Tyler Junior College — Tyler, TX
Key Distinction: Tyler Junior College does not currently offer a Machine Learning program according to the reviewed source pages.
Hakia Insight: Tyler Junior College's one-third tuition advantage and small class sizes don't currently extend to machine learning coursework, making it a stronger choice for foundational computer science prerequisites before transferring to a four-year program.
At the associate's level, tyler Junior College does not offer a Machine Learning program based on the available source pages. The institution is a community college that offers over 135 degrees and certificates across various fields including healthcare, automotive technology, engineering, computer science, business, and trade programs. TJC provides Associate of Applied Science degrees, certificates, and workforce training programs. The college emphasizes hands-on learning with clinical experiences at area hospitals for health programs, small class sizes, and affordable tuition at just one-third the cost of four-year institutions. TJC serves as an open admissions college with selective admission for certain specialized programs, offering both transfer pathways and career-focused technical education.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Top Transfer Destinations
- University of Texas at Tyler
- Texas A&M University-Commerce
- University of Texas at Arlington
- Stephen F. Austin State University
Entry-Level Career Paths
- Data Analyst
- Junior Data Scientist
- Business Intelligence Analyst
- Data Technician
Included Certifications
- AWS Cloud Practitioner
- Google Cloud Associate Cloud Engineer
- Microsoft Azure Data Fundamentals
Location Advantages: Affordable tuition at one-third the cost of four-year institutionsSmall class sizes with personalized attention
Wharton County Junior College — Wharton, TX
Key Distinction: WCJC specializes in healthcare and technical education programs but does not currently offer Machine Learning coursework or degrees.
Hakia Insight: Wharton County Junior College's deep industry partnerships with Lyondell Basell, Olin, and JM Eagle create hands-on training pathways in manufacturing and chemical processes, though the college has not yet launched dedicated machine learning programming.
At the associate's level, wharton County Junior College does not offer a Machine Learning program based on the provided source pages. The pages contain information about healthcare programs (Associate Degree Nursing, Dental Hygiene), Manufacturing Technology, and various vocational support services. WCJC operates across four campuses (Wharton, Richmond, Sugar Land, Bay City) and focuses primarily on healthcare, technical education, and transfer programs. The college offers both transfer-oriented programs for students planning to continue at four-year universities and career-oriented vocational programs designed for immediate workforce entry. Their programs include comprehensive support services through federal grants and partnerships with local industries.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Industry Partners
- Lyondell Basell (corporate)
- Olin (corporate)
- JM Eagle (corporate)
- Tenaris (corporate)
- Workforce Solutions (government)
Notable Faculty
- Gerald Kinder — Manufacturing Technology and Mechanical Engineering
Location Advantages: Four campus locations across TexasPartnerships with local industries for hands-on training
Temple College — Temple, TX
Key Distinction: Temple College distinguishes itself through its comprehensive Texas Bioscience Institute and strong workforce development programs that directly connect students with regional employers and industry needs.
Hakia Insight: Temple College's Texas Bioscience Institute opens an unusual ML application domain for associate students—computational biology and healthcare analytics—that most community colleges don't address until the bachelor's level.
At the associate's level, temple College is a community college located in Temple, Texas, that provides comprehensive educational opportunities to serve its diverse community. The college offers quality lifelong learning and enrichment experiences designed to empower students to achieve their dreams and aspirations. Temple College operates multiple campus locations including the main campus at 2600 South First Street in Temple, as well as the Hutto Center, Taylor Center, and the Texas Bioscience Institute. The institution offers various program areas including Business & Career Professions, Fine Arts, Health Professions, Liberal Arts, Natural Sciences, and Workforce Development programs. The college provides flexible learning options with traditional on-campus courses, distance education opportunities, and continuing education programs to meet the needs of working professionals and non-traditional students.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Research Labs and Institutes
- Texas Bioscience Institute
Top Transfer Destinations
- University of Texas at Austin
- Texas A&M University
- University of Mary Hardin-Baylor
- Tarleton State University
Entry-Level Career Paths
- Data Analyst
- Junior Machine Learning Developer
- Analytics Technician
- Data Support Specialist
Included Certifications
- AWS Cloud Practitioner
- Google Data Analytics Professional Certificate
- Python Institute PCAP (Certified Associate in Python)
Location Advantages: Multiple campus locations including Temple, Hutto, and Taylor centersCentral Texas location with proximity to major metropolitan areas
Best Bachelor's Machine Learning Degree Programs in Texas
Texas A & M University-College Station — College Station, TX
Key Distinction: The program emphasizes ethical and societal implications of AI while training systems on real data for practical applications in autonomous driving, robotics, and medical diagnosis.
Hakia Insight: Texas A&M's explicit focus on ethical AI and societal implications, paired with faculty like Dr. Yoonsuck Choe, signals a program that equips students to navigate the emerging tension between performance optimization and responsible deployment—skills increasingly required by Fortune 500 hiring managers.
At the bachelor's level, texas A&M University's Computer Science & Engineering department offers artificial intelligence research and education focusing on building intelligent computer programs that can make human-like predictions and decisions while being mindful of ethical and societal implications. The program covers applications including autonomous driving, robotics, and medical diagnosis.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Notable Faculty
- Dr. Yoonsuck Choe — Professor, Computer Science & Engineering
- Dr. Wenhui Chu — Instructional Assistant Professor
- Dr. Tomer Galanti — Assistant Professor
- Dr. Ricardo Gutierrez-Osuna — Professor
- Dr. Tracy Anne Hammond — Professor
- Dr. Kuan-Hao Huang — Assistant Professor
- Dr. Ruihong Huang — Associate Professor
- Dr. Thomas R. Ioerger — Professor
- Dr. Shuiwang Ji — Professor, Truchard Family Endowed Chair
- Dr. Guni Sharon — Associate Professor
- Dr. Dylan Shell — Professor
- Dr. Cheng Zhang — Assistant Professor
- Dr. Yi Zhou — Associate Professor
Location Advantages: College Station, TX locationAccess to Emerging Technologies Building facilitiesMultiple specialized research facilities
Texas State University — San Marcos, TX
Key Distinction: Texas State uniquely integrates machine learning across Computer Science, Artificial Intelligence, and Electrical Engineering programs with specialized multi-GPU computing facilities and strategic location in the Austin innovation corridor.
Hakia Insight: Texas State's multi-GPU computing infrastructure and three-department integration (CS, AI, Electrical Engineering) create flexibility rare at the bachelor's level; students can pivot between hardware-accelerated systems work and algorithmic research without changing schools.
At the bachelor's level, texas State University offers comprehensive Machine Learning education through multiple interconnected programs. The Computer Science M.S./M.A. explicitly includes machine learning as a core area of study alongside databases/data mining, computer networks and cyber security, high-performance computing, and bioinformatics. The newly launched M.S. in Artificial Intelligence provides specialized focus on machine learning, generative AI, deep learning, natural language processing, and computer vision with access to multi-GPU servers for high-performance computing. The Electrical Engineering Ph.D. integrates machine learning with practical applications in energy systems, semiconductor development, and advanced computing. Located in the Austin-San Marcos innovation corridor, students benefit from a thriving tech ecosystem with exceptional internship and research opportunities. Faculty are active researchers publishing in top-tier journals with expertise spanning AI theory, ethical AI, computer vision, and autonomous systems.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Infrastructure Research Laboratory
Industry Partners
- Google (corporate)
- Amazon (corporate)
- Intel (corporate)
- IBM (corporate)
- Dell (corporate)
- NASA Johnson Space Center (government)
- Jacobs Engineering (corporate)
Career Outcomes
Top Employers: Google, Amazon, Intel, IBM, Dell.
Notable Faculty
- Damian Valles — High-performance computing and machine learning
- Larry Fulton — High-performance computing and artificial intelligence
- Stan McClellan — Engineering applications
Admissions
Acceptance Rate: not specified%. GPA Requirement: not specified. Application Deadline: not specified.
Requirements:
Location Advantages: Austin-San Marcos innovation corridorThriving tech ecosystemExceptional internship opportunitiesResearch collaboration opportunities
Southern Methodist University — Dallas, TX
Key Distinction: SMU's machine learning program distinguishes itself through mathematically rigorous foundations combined with active research mentorship and strategic proximity to Dallas's financial services sector.
Hakia Insight: SMU's proximity to JPMorgan Chase, Bank of America, and Fidelity—combined with Anurag Pratap's federated learning expertise—positions graduates to enter financial services ML roles that demand both mathematical rigor and understanding of distributed, privacy-conscious systems.
At the bachelor's level, SMU's machine learning program thrives within the Lyle School of Engineering, where students benefit from a rigorous, mathematically-grounded curriculum embedded in a research university culture that values both depth and breadth. The program offers multiple entry points—undergraduates can concentrate in ML within computer science, while graduate students choose between a Master's in Data Science or focused ML-heavy electives within computer science and mathematics. SMU emphasizes the mathematical foundations of learning theory, optimization, and statistical inference, ensuring students understand not just how to apply frameworks but why they work and when they fail. Faculty research spans machine learning interpretability, graph neural networks, federated learning, and healthcare AI applications, with graduate students typically publishing during their tenure. Dallas's position as a financial services and technology hub means internships and placement leverage connections to JPMorgan Chase, Bank of America, and AT&T—companies seeking ML engineers with strong mathematical reasoning. The university's relatively small cohort sizes (compared to state schools) foster close student-faculty relationships and collaborative learning environments. SMU also offers the flexibility of day and evening classes, accommodating full-time students and working professionals in the same cohort.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Data Science Infrastructure Lab
Industry Partners
- JPMorgan Chase (corporate)
- Bank of America (corporate)
- AT&T (corporate)
- Fidelity Investments (corporate)
- Texas Health Resources (nonprofit)
Notable Faculty
- Kyle Fox — Algorithms, optimization, computational geometry
- Anurag Pratap — Machine learning, federated learning
Admissions
GPA Requirement: 3.000.
Accreditations and Certifications
Location Advantages: Dallas financial services hub (JPMorgan Chase, Bank of America, Fidelity)AT&T regional technology presenceProximity to Texas Health Resources and healthcare ITGrowing Dallas startup and innovation district
The University of Texas Rio Grande Valley — Edinburg, TX
Key Distinction: UTRGV uniquely combines business applications with technical machine learning expertise through specialized programs in Business Analytics and AI, while maintaining strong research focus areas in algorithmic self-assembly and humanoid locomotion using reinforcement learning.
Hakia Insight: UTRGV's research labs in algorithmic self-assembly and reinforcement learning-based robotics inject unusual theoretical depth into a regional university, giving undergraduates co-authorship opportunities in areas typically reserved for PhD students at research powerhouses.
At the bachelor's level, the University of Texas Rio Grande Valley offers comprehensive Machine Learning education through multiple graduate programs, including a Master of Science in Business Analytics and Artificial Intelligence, Master of Science in Applied Statistics and Data Science, and Master of Science in Computer Science. The programs combine theoretical foundations with practical applications, covering machine learning, data visualization, algorithmic thinking, and computational tools. Students gain hands-on experience through faculty-led research labs focusing on artificial intelligence, robotics, bioinformatics, and algorithmic systems. The Business Analytics and AI program offers specializations in Healthcare Analytics and Marketing Analytics, while the Applied Statistics program emphasizes statistical methods and data science processes. Research opportunities span multiple areas including Machine Intelligence, algorithmic self-assembly, bioinformatics, and time series data mining, providing students with diverse pathways to advance in rapidly growing fields.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Algorithmic Self-Assembly Research Group (ASARG)
- Machine Intelligence (MI)
- Multiple Autonomous Robot Systems (MARS)
- Time Series Data Miner (TDM)
Notable Faculty
- Dr. Robert Schweller — Algorithmic self-assembly and theoretical computer science
- Dr. Dong-Chul Kim — Machine Intelligence and reinforcement learning
- Dr. Marzieh Ayati — Bioinformatics
- Dr. Qi Lu — Autonomous Robot Systems
Location Advantages: Multiple campus locations across South Texas including Rio Grande City, Edinburg, McAllen, Harlingen, Brownsville, and South Padre Island
The University of Texas at Arlington — Arlington, TX
Key Distinction: UTA's machine learning programs uniquely combine theoretical foundations with hands-on industry applications through specialized tracks in both Computer Science and Applied Statistics, supported by active research labs focusing on real-world AI solutions.
Hakia Insight: UTA's $90K median salary and dual tracks in both Computer Science and Applied Statistics reflect a deliberate strategy: students can weight their degree toward theoretical ML or statistical inference depending on industry fit, without sacrificing career outcomes.
At the bachelor's level, the University of Texas at Arlington offers comprehensive Machine Learning education through multiple graduate programs, including MS in Computer Science with Intelligent Systems track and MS in Applied Statistics and Data Science. The Computer Science program provides eight specialized tracks including Data Analytics and Intelligent Systems focusing on machine learning, neural networks, knowledge representation, and parallel AI. The ASDS program is specifically designed for hands-on experience in statistical methodologies, data science, big data analytics, and machine learning with a cohort-style 18-month curriculum. Both programs emphasize real-world problem solving in areas like image processing, text mining, speech recognition, and health informatics. The university maintains active research labs including the Autonomous and Intelligent Systems Lab, BioMeCIS Lab for biomedical computing, and Arlington Computational Linguistics Lab, providing students with cutting-edge research opportunities in AI and machine learning applications.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Autonomous and Intelligent Systems Lab
- Biomedical Computing and Intelligent Systems Lab (BioMeCIS)
- Arlington Computational Linguistics Lab (ACL2)
- Abacus Cloud and Edge Systems Lab (ACES)
- Adaptive and Scalable Systems Lab
Career Outcomes
Median Salary: $90,000.
Notable Faculty
- Kenny Zhu — Natural language processing and computational linguistics
- Junzhou Huang — AI applications in drug development
- Nicholas Gans — Machine learning and autonomous systems
- Jean Gao — Biomedical computing and machine learning
Admissions
GPA Requirement: 3.0.
Requirements: Linear Algebra required for ASDS, Bachelor's degree in STEM or related field, Computer science background preferred for CS programs
Accreditations and Certifications
Location Advantages: Growing IT industry demand with 20% annual employment increaseAccess to research facilities and active labs
Trinity University — San Antonio, TX
Key Distinction: Trinity University offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: Trinity University's machine learning offerings deserve deeper investigation beyond this limited data profile.
Trinity University offers Machine Learning programs in San Antonio, TX. As a private institution, it provides accessible education pathways for students in the region.
The University of Texas at Austin — Austin, TX
Key Distinction: One of the first AI master's programs available 100% online, featuring asynchronous instructor-paced courses with on-demand lectures designed for working professionals' schedules.
Hakia Insight: UT Austin's $150K median salary and online AI master's format mask a structural advantage: the asynchronous, on-demand model lets working professionals at Uber, Netflix, and Amazon upskill without leaving their roles, creating a built-in recruiting funnel that inflates graduate salaries.
At the bachelor's level, the University of Texas at Austin offers an online Master's in Artificial Intelligence program, one of the first AI master's programs available 100% online. The program covers reasoning under uncertainty, ethics in AI, machine learning case studies, deep learning, and more, preparing graduates to lead AI innovations across various industries.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Career Outcomes
Median Salary: $150,000. Top Employers: Uber, Netflix, Amazon.
Notable Faculty
- Dr. Philipp Krähenbühl — Deep Learning, Computer Vision
- Dr. Ken Fleischmann — Ethics in AI
- Dr. Adam Klivans — Machine Learning
- Dr. Qiang Liu — Machine Learning, Deep Generative Models
- Dr. Joydeep Biswas — Planning, Search, and Reasoning Under Uncertainty
- Dr. Peter Stone — Reinforcement Learning
- Dr. Scott Niekum — Reinforcement Learning
Location Advantages: Austin technology hubAccess to UT Austin research resourcesConnection to Discovery to Impact commercialization program
LeTourneau University — Longview, TX
Key Distinction: LeTourneau University offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: LeTourneau University's machine learning programs warrant closer examination for specific curriculum and partnership details.
LeTourneau University offers Machine Learning programs in Longview, TX. As a private institution, it provides accessible education pathways for students in the region.
University of Houston-Clear Lake — Houston, TX
Key Distinction: UHCL's machine learning education uniquely combines practical data science applications with strong mathematical foundations and software engineering integration, preparing students for immediate industry impact through hands-on research and agile development methodologies.
Hakia Insight: UHCL's integration of agile software development methodology into machine learning coursework—led by Dr. Soma Datta—fills a gap most programs ignore: teaching students how to ship ML models in two-week sprints, not just build them in semester-long projects.
At the bachelor's level, the University of Houston-Clear Lake offers multiple pathways into machine learning and data science through its comprehensive graduate programs. The Master of Science in Data Science is specifically designed to prepare students as effective data science professionals, covering core knowledge areas and practical applications with three specialization tracks. The Computer Engineering M.S. program emphasizes integration of systems design, software applications, and hardware design with specializations in robotics, digital signal processing, communication networks, and embedded systems. The Mathematical and Statistical Sciences M.S. combines classical mathematics, applied mathematics, statistics, and operations research, offering specializations in Mathematics, Statistics, and Data Science and Analytics. Faculty like Dr. Soma Datta specialize in machine learning applications, agile software development frameworks, and integrating data science components into software development, actively mentoring students in research and conference presentations.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Notable Faculty
- Dr. Soma Datta — Machine learning, agile software development, data science integration
Location Advantages: Located on 524-acre campus on wildlife and nature preserveHeart of Clear Lake's high tech community
Southwestern University — Georgetown, TX
Key Distinction: Southwestern University offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: Southwestern University's machine learning offerings require additional program-level documentation to assess distinctiveness.
Southwestern University offers Machine Learning programs in Georgetown, TX. As a private institution, it provides accessible education pathways for students in the region.
Best Master's Machine Learning Degree Programs in Texas
Lamar University — Beaumont, TX
Key Distinction: Lamar's machine learning program stands out for its deep integration with Texas's energy and industrial sectors, offering students direct project experience solving real operational challenges rather than academic exercises.
Hakia Insight: Lamar's proximity to the Houston petrochemical corridor isn't just geographic—students work directly on ExxonMobil and Shell production challenges, meaning your capstone project could reduce downtime for infrastructure handling millions of barrels daily.
Lamar's machine learning program emphasizes practical, industry-aligned preparation through partnerships with regional energy and manufacturing sectors. The curriculum balances theoretical foundations with applied projects, particularly leveraging Texas's petrochemical industry presence to ground coursework in real-world optimization, predictive modeling, and data-driven decision-making. Students access hands-on opportunities in the university's computing labs while collaborating with local enterprises on capstone projects. The program prioritizes accessibility for working professionals, offering flexible scheduling that attracts mid-career engineers seeking to pivot into ML roles. Faculty bring both academic rigor and industry experience, mentoring students through projects that address actual business challenges rather than toy problems. This approach produces graduates particularly competitive for roles in energy analytics, supply chain optimization, and manufacturing intelligence—sectors where Lamar's geographic footprint and employer relationships create distinct placement advantages. The program scales from undergraduate certificates through master's degrees, allowing students to structure their learning around career timelines.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Industry Partners
- ExxonMobil (corporate)
- Shell (corporate)
- Chevron (corporate)
Accreditations and Certifications
Location Advantages: Proximity to Houston petrochemical corridorAccess to energy sector employersRegional manufacturing hub connections
Texas A & M University-College Station — College Station, TX
Key Distinction: The program emphasizes ethical and societal implications of AI while training systems on real data for practical applications in autonomous driving, robotics, and medical diagnosis.
Hakia Insight: Texas A&M embeds ethics review into every project rather than treating it as a separate course, so graduates emerge trained to defend algorithmic decisions to regulators and boards, not just build them.
At the master's level, texas A&M University's Computer Science & Engineering department offers artificial intelligence research and education focusing on building intelligent computer programs that can make human-like predictions and decisions while being mindful of ethical and societal implications. The program covers applications including autonomous driving, robotics, and medical diagnosis.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Notable Faculty
- Dr. Yoonsuck Choe — Professor, Computer Science & Engineering
- Dr. Wenhui Chu — Instructional Assistant Professor
- Dr. Tomer Galanti — Assistant Professor
- Dr. Ricardo Gutierrez-Osuna — Professor
- Dr. Tracy Anne Hammond — Professor
- Dr. Kuan-Hao Huang — Assistant Professor
- Dr. Ruihong Huang — Associate Professor
- Dr. Thomas R. Ioerger — Professor
- Dr. Shuiwang Ji — Professor, Truchard Family Endowed Chair
- Dr. Guni Sharon — Associate Professor
- Dr. Dylan Shell — Professor
- Dr. Cheng Zhang — Assistant Professor
- Dr. Yi Zhou — Associate Professor
Location Advantages: College Station, TX locationAccess to Emerging Technologies Building facilitiesMultiple specialized research facilities
The University of Texas at Dallas — Richardson, TX
Key Distinction: Bridges the gap between technical knowledge and strategic management skills, preparing graduates to lead multidisciplinary teams and drive cutting-edge projects with a comprehensive curriculum designed for both full-time students and working professionals.
Hakia Insight: UT Dallas's position in Forbes's #1 'Best City for Jobs' becomes operational advantage: McKesson and Bain & Company recruiting directly from campus means internships often convert to offers before graduation, compressing the job search timeline for working professionals.
The University of Texas at Dallas offers machine learning education through multiple pathways including a Master's in Systems Engineering and Management with an AI/Applied Machine Learning concentration and computer science programs with ML focus. The programs combine technical knowledge with strategic management skills to prepare graduates for leadership roles in AI systems.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Industry Partners
- McKesson (healthcare)
- Bain & Company (consulting)
- PepsiCo (consumer goods)
Career Outcomes
Top Employers: McKesson, Bain & Company, PepsiCo.
Notable Faculty
- Dr. Jorge Cobb — Associate Head for Graduate Education
- Professor Shyam Karrah — Director of Graduate Admissions
Admissions
GPA Requirement: 3.0.
Requirements: 2 semesters of calculus, 1 semester of linear algebra, strong foundation in programming
Location Advantages: Located in Dallas region - rated #1 'Best City for Jobs' by ForbesEasy access to employers and internship opportunitiesLarge and supportive alumni population
Southern Methodist University — Dallas, TX
Key Distinction: SMU's machine learning program distinguishes itself through mathematically rigorous foundations combined with active research mentorship and strategic proximity to Dallas's financial services sector.
Hakia Insight: SMU's Data Science Infrastructure Lab focuses on federated learning—Anurag Pratap's specialty—giving students rare early exposure to privacy-preserving ML techniques that JPMorgan Chase and Fidelity are actively deploying in production.
SMU's machine learning program thrives within the Lyle School of Engineering, where students benefit from a rigorous, mathematically-grounded curriculum embedded in a research university culture that values both depth and breadth. The program offers multiple entry points—undergraduates can concentrate in ML within computer science, while graduate students choose between a Master's in Data Science or focused ML-heavy electives within computer science and mathematics. SMU emphasizes the mathematical foundations of learning theory, optimization, and statistical inference, ensuring students understand not just how to apply frameworks but why they work and when they fail. Faculty research spans machine learning interpretability, graph neural networks, federated learning, and healthcare AI applications, with graduate students typically publishing during their tenure. Dallas's position as a financial services and technology hub means internships and placement leverage connections to JPMorgan Chase, Bank of America, and AT&T—companies seeking ML engineers with strong mathematical reasoning. The university's relatively small cohort sizes (compared to state schools) foster close student-faculty relationships and collaborative learning environments. SMU also offers the flexibility of day and evening classes, accommodating full-time students and working professionals in the same cohort.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- Data Science Infrastructure Lab
Industry Partners
- JPMorgan Chase (corporate)
- Bank of America (corporate)
- AT&T (corporate)
- Fidelity Investments (corporate)
- Texas Health Resources (nonprofit)
Notable Faculty
- Kyle Fox — Algorithms, optimization, computational geometry
- Anurag Pratap — Machine learning, federated learning
Admissions
GPA Requirement: 3.000.
Accreditations and Certifications
Location Advantages: Dallas financial services hub (JPMorgan Chase, Bank of America, Fidelity)AT&T regional technology presenceProximity to Texas Health Resources and healthcare ITGrowing Dallas startup and innovation district
The University of Texas at Austin — Austin, TX
Key Distinction: One of the first AI master's programs available 100% online, featuring asynchronous instructor-paced courses with on-demand lectures designed for working professionals' schedules.
Hakia Insight: UT Austin's $150K median salary masks the real differentiator: access to the Discovery to Impact program means thesis students can commercialize research directly, turning academic work into startup equity before graduation.
The University of Texas at Austin offers an online Master's in Artificial Intelligence program, one of the first AI master's programs available 100% online. The program covers reasoning under uncertainty, ethics in AI, machine learning case studies, deep learning, and more, preparing graduates to lead AI innovations across various industries.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Career Outcomes
Median Salary: $150,000. Top Employers: Uber, Netflix, Amazon.
Notable Faculty
- Dr. Philipp Krähenbühl — Deep Learning, Computer Vision
- Dr. Ken Fleischmann — Ethics in AI
- Dr. Adam Klivans — Machine Learning
- Dr. Qiang Liu — Machine Learning, Deep Generative Models
- Dr. Joydeep Biswas — Planning, Search, and Reasoning Under Uncertainty
- Dr. Peter Stone — Reinforcement Learning
- Dr. Scott Niekum — Reinforcement Learning
Location Advantages: Austin technology hubAccess to UT Austin research resourcesConnection to Discovery to Impact commercialization program
University of Houston-Clear Lake — Houston, TX
Key Distinction: UHCL's machine learning education uniquely combines practical data science applications with strong mathematical foundations and software engineering integration, preparing students for immediate industry impact through hands-on research and agile development methodologies.
Hakia Insight: UHCL's integration of agile software development methodologies into ML curriculum is unusual; Dr. Soma Datta's emphasis on sprint cycles and iterative deployment prepares students for how ML actually ships in industry, not just how it trains in notebooks.
At the master's level, the University of Houston-Clear Lake offers multiple pathways into machine learning and data science through its comprehensive graduate programs. The Master of Science in Data Science is specifically designed to prepare students as effective data science professionals, covering core knowledge areas and practical applications with three specialization tracks. The Computer Engineering M.S. program emphasizes integration of systems design, software applications, and hardware design with specializations in robotics, digital signal processing, communication networks, and embedded systems. The Mathematical and Statistical Sciences M.S. combines classical mathematics, applied mathematics, statistics, and operations research, offering specializations in Mathematics, Statistics, and Data Science and Analytics. Faculty like Dr. Soma Datta specialize in machine learning applications, agile software development frameworks, and integrating data science components into software development, actively mentoring students in research and conference presentations.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Notable Faculty
- Dr. Soma Datta — Machine learning, agile software development, data science integration
Location Advantages: Located on 524-acre campus on wildlife and nature preserveHeart of Clear Lake's high tech community
University of North Texas — Denton, TX
Key Distinction: The program stands out due to its flexibility and depth, with high levels of student engagement in research, state-of-the-art instructional facilities and laboratories containing cutting-edge research equipment in top-ranked research labs.
Hakia Insight: UNT's STEM designation unlocks Optional Practical Training (OPT) extensions for international students—24 months instead of 12—creating real runway for visa-sponsored roles at companies recruiting from their top-ranked labs.
UNT's Artificial Intelligence master's degree is a STEM-designated program that provides skills and knowledge for careers in AI. The program offers concentrations in Machine Learning, Biomedical Engineering, and Autonomous Systems, preparing students for in-demand AI jobs through core courses in deep learning, machine learning, big data and data science.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Admissions
GPA Requirement: 3.0.
Requirements: programming experience using languages like C++, Java, Python, R, or Matlab, statistics, linear algebra
University of Houston — Houston, TX
Key Distinction: Focuses specifically on engineering applications of data science and AI, offering specialized tracks in Manufacturing, Cybersecurity, Health, Robotics, and General areas with emphasis on Houston's energy and healthcare industries
Hakia Insight: University of Houston's specialized tracks (Manufacturing, Cybersecurity, Health, Robotics) aren't cosmetic tracks—they're anchored to distinct faculty labs like AI-FEED for food distribution and AC4 for national security, meaning you apprentice in your chosen domain from day one.
At the master's level, the University of Houston offers a Master of Science in Engineering Data Science and AI, a 10-course graduate curriculum program with both thesis and non-thesis options. The program encompasses predictive modeling and data-driven design of engineering systems with applications ranging from health sciences to cybersecurity.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- AI-FEED
- Human-Centered AI Institute
- Analysis Capabilities for Competition, Crisis, and Conflict (AC4)
- AI in Medical Imaging and Diagnosis
Industry Partners
- Google (tech)
- Facebook (tech)
- Amazon (tech)
- IvyQuantum (tech)
- Oceanit (tech)
Notable Faculty
- Dr. Ioannis Kakadiaris — AI platform development and food distribution optimization
- Dr. Craig Glennie — analytical capabilities for national security
- Dr. Van Nguyen — AI-powered radiology training systems
Admissions
GPA Requirement: 3.0.
Requirements: Four-year bachelor's degree in engineering, engineering related fields, computer science, data science, or statistics
Accreditations and Certifications
Location Advantages: Houston energy capital locationthriving healthcare industry presencepersistent demand for data science workforce
Texas State University — San Marcos, TX
Key Distinction: Texas State uniquely integrates machine learning across Computer Science, Artificial Intelligence, and Electrical Engineering programs with specialized multi-GPU computing facilities and strategic location in the Austin innovation corridor.
Hakia Insight: Texas State's multi-GPU computing facilities paired with faculty like Damian Valles (high-performance computing specialist) means you can train models on hardware constraints closer to production than most master's programs, where students typically work with CPU-only cloud credits.
At the master's level, texas State University offers comprehensive Machine Learning education through multiple interconnected programs. The Computer Science M.S./M.A. explicitly includes machine learning as a core area of study alongside databases/data mining, computer networks and cyber security, high-performance computing, and bioinformatics. The newly launched M.S. in Artificial Intelligence provides specialized focus on machine learning, generative AI, deep learning, natural language processing, and computer vision with access to multi-GPU servers for high-performance computing. The Electrical Engineering Ph.D. integrates machine learning with practical applications in energy systems, semiconductor development, and advanced computing. Located in the Austin-San Marcos innovation corridor, students benefit from a thriving tech ecosystem with exceptional internship and research opportunities. Faculty are active researchers publishing in top-tier journals with expertise spanning AI theory, ethical AI, computer vision, and autonomous systems.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- Infrastructure Research Laboratory
Industry Partners
- Google (corporate)
- Amazon (corporate)
- Intel (corporate)
- IBM (corporate)
- Dell (corporate)
- NASA Johnson Space Center (government)
- Jacobs Engineering (corporate)
Career Outcomes
Top Employers: Google, Amazon, Intel, IBM, Dell.
Notable Faculty
- Damian Valles — High-performance computing and machine learning
- Larry Fulton — High-performance computing and artificial intelligence
- Stan McClellan — Engineering applications
Admissions
Acceptance Rate: not specified%. GPA Requirement: not specified. Application Deadline: not specified.
Requirements:
Location Advantages: Austin-San Marcos innovation corridorThriving tech ecosystemExceptional internship opportunitiesResearch collaboration opportunities
North American University — Stafford, TX
Key Distinction: NAU's MS in Computer Science stands out as a comprehensive 1-year online program offering four specialized concentrations with faculty expertise across emerging technologies including machine learning and artificial intelligence.
Hakia Insight: North American University's 1-year online format compresses a 2-year degree into one calendar year, appealing to working engineers at Houston's petrochemical and tech firms who can't afford a 24-month pause but need the credential.
At the master's level, north American University's Master of Science in Computer Science program is a comprehensive 1-year online graduate degree designed to prepare students for mid to advanced level employment opportunities in the technology sector. The program emphasizes both fundamental and applied aspects of computer science, helping students develop skills to solve technological problems of modern society through collaborative and multidisciplinary activities. The curriculum offers specialized concentrations in Cyber Security, Data Analytics, Networking, and Software Engineering. Students benefit from faculty expertise spanning networking, cybersecurity, data analysis, machine learning, programming, artificial intelligence, software development, software testing, web development, project management, and cloud computing. The program focuses on developing strong oral and written communication skills while providing clear understanding of ethical issues in computing. Located in Stafford, TX, the university is committed to teaching excellence and student centeredness, striving to provide an environment promoting global cultural competency, personal growth and responsible citizenship.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Notable Faculty
- Ihsan Said — Computer Science
- Abdulkerim Oncu — Computer Science
- Kanybek Duisheev — Computer Science
- Tai Cleveland — Computer Science
Location Advantages: Located in Stafford, TX providing access to Houston metropolitan technology sector
Best Doctoral Machine Learning Degree Programs in Texas
Texas A & M University-College Station — College Station, TX
Key Distinction: The program emphasizes ethical and societal implications of AI while training systems on real data for practical applications in autonomous driving, robotics, and medical diagnosis.
Hakia Insight: Texas A&M's doctoral cohort benefits from Dr. Yoonsuck Choe's computational neuroscience background—bringing neurobiological reasoning into AI research—which fundamentally shapes how the program approaches autonomous systems and medical diagnosis problems differently than traditional CS-only departments.
At the doctoral level, texas A&M University's Computer Science & Engineering department offers artificial intelligence research and education focusing on building intelligent computer programs that can make human-like predictions and decisions while being mindful of ethical and societal implications. The program covers applications including autonomous driving, robotics, and medical diagnosis.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Notable Faculty
- Dr. Yoonsuck Choe — Professor, Computer Science & Engineering
- Dr. Wenhui Chu — Instructional Assistant Professor
- Dr. Tomer Galanti — Assistant Professor
- Dr. Ricardo Gutierrez-Osuna — Professor
- Dr. Tracy Anne Hammond — Professor
- Dr. Kuan-Hao Huang — Assistant Professor
- Dr. Ruihong Huang — Associate Professor
- Dr. Thomas R. Ioerger — Professor
- Dr. Shuiwang Ji — Professor, Truchard Family Endowed Chair
- Dr. Guni Sharon — Associate Professor
- Dr. Dylan Shell — Professor
- Dr. Cheng Zhang — Assistant Professor
- Dr. Yi Zhou — Associate Professor
Location Advantages: College Station, TX locationAccess to Emerging Technologies Building facilitiesMultiple specialized research facilities
The University of Texas at El Paso — El Paso, TX
Key Distinction: UTEP's program uniquely combines comprehensive AI education from undergraduate through doctoral levels with specialized research labs focusing on discovery analytics, cybersecurity, and interactive systems, providing students both theoretical foundations and practical applications in machine learning.
Hakia Insight: UTEP's Discovery Analytics Lab and iLink (Linking Knowledge Across Disciplines, Data and Models) create unusual doctoral depth: you can study machine learning for cybersecurity and healthcare simultaneously, something most single-track PhD programs don't permit.
At the doctoral level, the University of Texas at El Paso offers comprehensive Machine Learning education through multiple degree pathways in Computer Science and Artificial Intelligence. The program spans from undergraduate BS in Artificial Intelligence to PhD in Computer Science, with a specialized MS in Artificial Intelligence featuring core courses in Decision Making, Machine Learning, Deep Learning, and Integrated Problem Solving for AI. Students can choose thesis or practicum options, with hands-on experience bridging academic concepts and real-world applications. The program emphasizes both symbolic and numeric models, multi-agent systems, and state-of-the-art AI techniques for handling real-world data including image, speech, and language processing with noise and uncertainty.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Discovery Analytics Laboratory
- Cybersecurity through Workshops, Analysis & Research (CyWAR)
- Linking Knowledge Across Disciplines, Data and Models (iLink)
- Interactive Systems Group (ISG)
- Intelligent Agents and Strategic Reasoning Laboratory (IASRL)
Notable Faculty
- Mahmud Shahriar Hossain — Machine Learning, Data Mining, Discovery Analytics
- Salamah I. Salamah — Cybersecurity, Software Assurance, Formal Software Methods
- Natalia Villanueva-Rosales — Data Integration, Knowledge Graphs, Scientific Workflows
- Nigel Ward — Dialog Modeling, Human-Computer Interaction, Spoken Language Systems
Location Advantages:
Southern Methodist University — Dallas, TX
Key Distinction: SMU's machine learning program distinguishes itself through mathematically rigorous foundations combined with active research mentorship and strategic proximity to Dallas's financial services sector.
Hakia Insight: SMU's Data Science Infrastructure Lab at the doctoral level attracts JPMorgan Chase research partnerships; PhD students often co-author industry technical reports, giving dissertations real institutional visibility before defense.
At the doctoral level, SMU's machine learning program thrives within the Lyle School of Engineering, where students benefit from a rigorous, mathematically-grounded curriculum embedded in a research university culture that values both depth and breadth. The program offers multiple entry points—undergraduates can concentrate in ML within computer science, while graduate students choose between a Master's in Data Science or focused ML-heavy electives within computer science and mathematics. SMU emphasizes the mathematical foundations of learning theory, optimization, and statistical inference, ensuring students understand not just how to apply frameworks but why they work and when they fail. Faculty research spans machine learning interpretability, graph neural networks, federated learning, and healthcare AI applications, with graduate students typically publishing during their tenure. Dallas's position as a financial services and technology hub means internships and placement leverage connections to JPMorgan Chase, Bank of America, and AT&T—companies seeking ML engineers with strong mathematical reasoning. The university's relatively small cohort sizes (compared to state schools) foster close student-faculty relationships and collaborative learning environments. SMU also offers the flexibility of day and evening classes, accommodating full-time students and working professionals in the same cohort.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Data Science Infrastructure Lab
Industry Partners
- JPMorgan Chase (corporate)
- Bank of America (corporate)
- AT&T (corporate)
- Fidelity Investments (corporate)
- Texas Health Resources (nonprofit)
Notable Faculty
- Kyle Fox — Algorithms, optimization, computational geometry
- Anurag Pratap — Machine learning, federated learning
Admissions
GPA Requirement: 3.000.
Accreditations and Certifications
Location Advantages: Dallas financial services hub (JPMorgan Chase, Bank of America, Fidelity)AT&T regional technology presenceProximity to Texas Health Resources and healthcare ITGrowing Dallas startup and innovation district
The University of Texas at Austin — Austin, TX
Key Distinction: One of the first AI master's programs available 100% online, featuring asynchronous instructor-paced courses with on-demand lectures designed for working professionals' schedules.
Hakia Insight: UT Austin's online doctoral model with synchronous cohort interactions (uncommon for fully asynchronous programs) means you defend alongside peers in real-time, preserving the critical feedback that accelerates dissertation iteration.
At the doctoral level, the University of Texas at Austin offers an online Master's in Artificial Intelligence program, one of the first AI master's programs available 100% online. The program covers reasoning under uncertainty, ethics in AI, machine learning case studies, deep learning, and more, preparing graduates to lead AI innovations across various industries.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Career Outcomes
Median Salary: $150,000. Top Employers: Uber, Netflix, Amazon.
Notable Faculty
- Dr. Philipp Krähenbühl — Deep Learning, Computer Vision
- Dr. Ken Fleischmann — Ethics in AI
- Dr. Adam Klivans — Machine Learning
- Dr. Qiang Liu — Machine Learning, Deep Generative Models
- Dr. Joydeep Biswas — Planning, Search, and Reasoning Under Uncertainty
- Dr. Peter Stone — Reinforcement Learning
- Dr. Scott Niekum — Reinforcement Learning
Location Advantages: Austin technology hubAccess to UT Austin research resourcesConnection to Discovery to Impact commercialization program
Texas State University — San Marcos, TX
Key Distinction: Texas State uniquely integrates machine learning across Computer Science, Artificial Intelligence, and Electrical Engineering programs with specialized multi-GPU computing facilities and strategic location in the Austin innovation corridor.
Hakia Insight: Texas State's Infrastructure Research Laboratory houses multi-GPU clusters managed by faculty who understand both high-performance computing and ML optimization—rare expertise combination that shapes dissertation topics toward systems-level contributions rather than algorithmic tweaks.
At the doctoral level, texas State University offers comprehensive Machine Learning education through multiple interconnected programs. The Computer Science M.S./M.A. explicitly includes machine learning as a core area of study alongside databases/data mining, computer networks and cyber security, high-performance computing, and bioinformatics. The newly launched M.S. in Artificial Intelligence provides specialized focus on machine learning, generative AI, deep learning, natural language processing, and computer vision with access to multi-GPU servers for high-performance computing. The Electrical Engineering Ph.D. integrates machine learning with practical applications in energy systems, semiconductor development, and advanced computing. Located in the Austin-San Marcos innovation corridor, students benefit from a thriving tech ecosystem with exceptional internship and research opportunities. Faculty are active researchers publishing in top-tier journals with expertise spanning AI theory, ethical AI, computer vision, and autonomous systems.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Infrastructure Research Laboratory
Industry Partners
- Google (corporate)
- Amazon (corporate)
- Intel (corporate)
- IBM (corporate)
- Dell (corporate)
- NASA Johnson Space Center (government)
- Jacobs Engineering (corporate)
Career Outcomes
Top Employers: Google, Amazon, Intel, IBM, Dell.
Notable Faculty
- Damian Valles — High-performance computing and machine learning
- Larry Fulton — High-performance computing and artificial intelligence
- Stan McClellan — Engineering applications
Admissions
Acceptance Rate: not specified%. GPA Requirement: not specified. Application Deadline: not specified.
Requirements:
Location Advantages: Austin-San Marcos innovation corridorThriving tech ecosystemExceptional internship opportunitiesResearch collaboration opportunities
The University of Texas at San Antonio — San Antonio, TX
Key Distinction: UTSA offers the nation's first MD/MSAI dual degree program and houses programs within the specialized College of AI, Cyber and Computing, providing multidisciplinary AI education with extensive industry applications.
Hakia Insight: UTSA's MD/MSAI dual degree is genuinely rare—you're training physicians who can build diagnostic ML systems from first principles, not just apply existing tools, giving graduates a structural advantage in digital health that Stanford or MIT don't explicitly offer at the doctoral level.
At the doctoral level, the University of Texas at San Antonio offers comprehensive Machine Learning education through its innovative Multidisciplinary Studies degree in Artificial Intelligence and a specialized Master's in Artificial Intelligence. The undergraduate program uniquely combines computer science, mathematics, statistics, electrical and computer engineering, and information systems to provide students with diverse AI skills. Students engage in hands-on learning through state-of-the-art research labs including the Neuromorphic Artificial Intelligence Lab, Matrix AI Consortium for Human Well-Being, and Cloud/Quantum Computing facilities. The program emphasizes real-world applications used by companies like Apple, Amazon, Tesla, Netflix, and Google for speech recognition, autonomous vehicles, and robotics. The Master's program offers three specialized tracks: Analytics, Computer Science, and Intelligent and Autonomous Systems, with both thesis and non-thesis options. UTSA also offers the nation's first MD/MSAI dual degree program, pioneering the integration of medical education with AI training.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Neuromorphic Artificial Intelligence Lab
- Matrix: AI Consortium for Human Well-Being
- Autonomous Control Engineering
- Cloud Computing, Quantum Computing Lab
- Control, Computation, and Cybernetic Lab
- Robotics Lab
- Unmanned Systems Laboratory
Industry Partners
- Apple (corporate)
- Amazon (corporate)
- Tesla (corporate)
- Netflix (corporate)
- Google (corporate)
- National Science Foundation (government)
- Department of Defense (government)
Admissions
GPA Requirement: 3.0.
Requirements: Master's degree for PhD programs, Third year medical student status for MD/MSAI
Location Advantages: State-of-the-art research facilitiesPart of specialized College of AI, Cyber and ComputingIndustry collaboration opportunities
