Best Associate's Machine Learning Degree Programs in Utah
Weber State University — Ogden, UT
Key Distinction: Weber State delivers practical machine learning education tailored to working professionals and career-changers, with strong regional industry partnerships and flexible scheduling.
Hakia Insight: Weber State's proximity to Hill Air Force Base contractors creates an unusual pipeline: defense-adjacent ML roles (autonomous systems, signal processing) that typically require security clearances—a credential multiplier most community colleges never access.
At the associate's level, weber State's computer science program integrates machine learning into a practical, applications-focused curriculum where students learn to build and deploy models rather than dwell exclusively on mathematical theory. The program reflects Weber State's mission as an open-access institution—accessible to students from varied mathematical backgrounds—while maintaining professional standards through capstone projects and industry partnerships in Northern Utah's tech sector. Coursework in machine learning, data science, and intelligent systems emphasizes hands-on implementation using Python, TensorFlow, and scikit-learn alongside explanation of underlying concepts; graduates are competent in both the engineering and the reasoning. Faculty maintain active connections to employers in the Ogden and Salt Lake City areas, resulting in guest lectures, project sponsorships, and direct internship pipelines into companies like Hill Air Force Base contractors and regional tech firms. The BS in Computer Science and related Data Science programs attract returning adults and transfer students, with scheduling flexibility and support services designed for diverse student populations. Capstone experiences often partner with local businesses—predictive maintenance for manufacturing, customer churn modeling, inventory optimization—giving students portfolio pieces that directly address employer needs. The university's location in the Ogden-Layton corridor places graduates within easy reach of defense, aerospace, and advanced manufacturing sectors where ML application is growing, alongside traditional tech hiring. Weber State graduates typically pursue data analyst, junior ML engineer, and analytics roles at mid-market companies, government contractors, and regional tech startups rather than FAANG research pipelines, though strong students transition into those paths via industry experience.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Industry Partners
- Hill Air Force Base (government)
- Autoliv (corporate)
- Various Northern Utah tech startups (startup)
Career Outcomes
Top Employers: Hill Air Force Base contractors, Regional tech companies, Manufacturing firms.
Location Advantages: Proximity to Hill Air Force Base and defense contractors; access to Ogden-Layton tech ecosystem; regional manufacturing and advanced manufacturing sectors
Utah Valley University — Orem, UT
Key Distinction: Utah Valley University delivers machine learning education tightly integrated with Utah's software industry, offering students unmatched access to internships and entry-level roles in one of the nation's fastest-growing tech regions.
Hakia Insight: Utah Valley's tight integration with Adobe, Microsoft, and Oracle means internships often convert directly into junior roles before graduation; regional hiring velocity is so high that employers actively recruit from the program rather than waiting for job applications.
At the associate's level, utah Valley University's computer science program has rapidly grown its machine learning offerings in response to local demand, positioning the curriculum to serve the needs of students entering Utah's booming tech corridor. The program emphasizes practical skill-building—students learn Python, TensorFlow, and scikit-learn early and often, applying these tools to datasets from real coursework projects by year two. Machine learning courses include applications in classification, clustering, time-series forecasting, and recommendation systems, with electives in natural language processing and computer vision. The University's location in Utah County, home to a dense cluster of software and tech companies (including major operations by Adobe, Microsoft, and Oracle), creates direct employment pipelines and summer internship channels that are unmatched for regional students. Many instructors maintain part-time roles at local tech firms, keeping curriculum relevant and creating mentorship bridges to industry. UVU's commitment to affordable, accessible education means many graduates remain in the Utah region, building a strong alumni network in local tech companies. The program suits students who want solid ML competency, quick time-to-employment, and career growth within Utah's thriving tech ecosystem.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Industry Partners
- Adobe (corporate)
- Microsoft (corporate)
- Oracle (corporate)
Career Outcomes
Top Employers: Adobe, Microsoft, Oracle, Local Utah tech startups.
Location Advantages: Proximity to Utah County tech corridorDirect partnerships with Adobe, Microsoft, OracleHigh regional hiring demand for ML graduates
Snow College — Ephraim, UT
Hakia Insight: Snow College's intimate class sizes aren't just pedagogically pleasant—instructors maintain direct relationships with regional employers, meaning your capstone project can become a paid contract or internship offer before you graduate.
At the associate's level, in Snow's intimate classroom setting, you get individual attention from instructors who know machine learning industry trends firsthand—not lecture halls where you're one of hundreds. The program balances core computer science fundamentals with applied machine learning coursework, ensuring you understand not just how to use tools but why they work. Snow's location in central Utah serves students from rural and semi-rural areas who might not have easy access to larger institutions, and the college actively supports transfer students moving to four-year programs at Utah universities. Graduates typically move into data technician roles, junior analyst positions, or continue their education while working part-time. The smaller cohort size means better networking and stronger faculty mentorship throughout your studies.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Career Outcomes
Top Employers: Sanpete County employers, Regional healthcare systems, State government IT departments, Online and remote-first tech companies.
Top Transfer Destinations
- University of Utah
- Utah State University
- Southern Utah University
Entry-Level Career Paths
- Junior Data Analyst
- Machine Learning Support Technician
- Data Processing Technician
- Business Intelligence Associate
- IT Support Specialist (data-focused)
Included Certifications
- AWS Certified Cloud Practitioner
- CompTIA A+
- Google Cloud Fundamentals
Location Advantages:
Best Bachelor's Machine Learning Degree Programs in Utah
Western Governors University — Salt Lake City, UT
Key Distinction: WGU's competency-based, self-paced model allows students to prove mastery rather than accumulate credits, making it the fastest path for working professionals into data roles.
Hakia Insight: WGU's competency-based model lets you accelerate through foundational material you already know (if you're coming from IT support or data entry) and decelerate on genuinely novel topics, compressing a 4-year degree into 18-24 months for focused learners—a real speed advantage competitors can't match.
At the bachelor's level, WGU's competency-based approach to machine learning education fundamentally reshapes how students progress through technical material—you advance by demonstrating mastery rather than accumulating credits or seat time. This model suits working professionals and self-directed learners who want to accelerate through familiar concepts while investing deeper time in challenging material. The Bachelor of Science in Data Management/Analytics and Master of Science in Data Analytics emphasize practical application immediately; courses integrate real datasets and industry-standard tools (Python, R, SQL, Tableau) from day one rather than theoretical foundations divorced from implementation. WGU's online-first infrastructure means no geographic constraints, and the flat-rate tuition model eliminates per-credit penalties for students who need extra support on complex topics like neural networks or statistical modeling. The program pairs written coursework with capstone projects where students work on problems mirroring actual business challenges—predictive modeling for operations, customer segmentation, anomaly detection. Faculty are primarily practitioners and industry veterans rather than pure academics, which shapes curriculum design toward skills employers actually hire for. Completion timelines vary widely (some students finish in 18 months, others take 3+ years) because pacing is genuinely self-directed; this flexibility attracts career-changers and those balancing education with full-time work. WGU's outcomes data highlights strong placement in data analyst, business intelligence, and junior data scientist roles at mid-market companies and Fortune 500 corporations, though the program stops short of the research-intensive preparation needed for PhD tracks or cutting-edge ML research labs.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages: No geographic constraints; fully online accessibility
Weber State University — Ogden, UT
Key Distinction: Weber State delivers practical machine learning education tailored to working professionals and career-changers, with strong regional industry partnerships and flexible scheduling.
Hakia Insight: Weber State's partnership with Hill Air Force Base contractors gives you access to advanced manufacturing ML problems (predictive maintenance, anomaly detection in sensor data) that most bachelor's programs only see in case studies, not live datasets.
At the bachelor's level, weber State's computer science program integrates machine learning into a practical, applications-focused curriculum where students learn to build and deploy models rather than dwell exclusively on mathematical theory. The program reflects Weber State's mission as an open-access institution—accessible to students from varied mathematical backgrounds—while maintaining professional standards through capstone projects and industry partnerships in Northern Utah's tech sector. Coursework in machine learning, data science, and intelligent systems emphasizes hands-on implementation using Python, TensorFlow, and scikit-learn alongside explanation of underlying concepts; graduates are competent in both the engineering and the reasoning. Faculty maintain active connections to employers in the Ogden and Salt Lake City areas, resulting in guest lectures, project sponsorships, and direct internship pipelines into companies like Hill Air Force Base contractors and regional tech firms. The BS in Computer Science and related Data Science programs attract returning adults and transfer students, with scheduling flexibility and support services designed for diverse student populations. Capstone experiences often partner with local businesses—predictive maintenance for manufacturing, customer churn modeling, inventory optimization—giving students portfolio pieces that directly address employer needs. The university's location in the Ogden-Layton corridor places graduates within easy reach of defense, aerospace, and advanced manufacturing sectors where ML application is growing, alongside traditional tech hiring. Weber State graduates typically pursue data analyst, junior ML engineer, and analytics roles at mid-market companies, government contractors, and regional tech startups rather than FAANG research pipelines, though strong students transition into those paths via industry experience.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Industry Partners
- Hill Air Force Base (government)
- Autoliv (corporate)
- Various Northern Utah tech startups (startup)
Career Outcomes
Top Employers: Hill Air Force Base contractors, Regional tech companies, Manufacturing firms.
Location Advantages: Proximity to Hill Air Force Base and defense contractors; access to Ogden-Layton tech ecosystem; regional manufacturing and advanced manufacturing sectors
Brigham Young University — Provo, UT
Key Distinction: Choice between Data Science Capstone sequence or undergraduate research. Undergraduate research option allowing two semesters for 6 credits total
Hakia Insight: BYU's two-semester research option lets you co-author publishable work in computer vision or robotics labs—unusual for undergrads—creating a tangible credential (published papers) that separates you in tech hiring beyond GPA and projects.
BYU's Bachelor of Science in Machine Learning is a comprehensive 74-credit program combining computer science fundamentals with advanced machine learning theory and applications. The curriculum includes core CS courses like data structures and algorithms, followed by specialized ML courses including Introduction to Machine Learning, Advanced Machine Learning, and Deep Learning. Students choose from specialization areas including computer vision, natural language processing, artificial intelligence, and optimization. The program offers flexible capstone options: either a two-semester Data Science Capstone sequence or undergraduate research opportunities. Students complete 9 additional credit hours from advanced electives in areas like graph data science, Bayesian statistics, and predictive modeling theory. The program emphasizes both theoretical foundations through mathematics requirements (calculus, linear algebra, statistics) and practical implementation skills. A senior exit interview ensures career readiness for professional ML roles or graduate school preparation.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus. BS
Research Labs and Institutes
- Computer Vision and Image Processing Lab
- Robotics and Automation Lab
Industry Partners
- Microsoft (corporate)
- Adobe (corporate)
- Google (corporate)
- Apple (corporate)
Career Outcomes
Top Employers: Microsoft, Adobe, Google, Apple, Meta, Amazon.
Notable Faculty
- Jeff Phillips — Machine learning algorithms, data mining, clustering
- Parris Egbert — Computer vision, image processing, graphics
Accreditations and Certifications
Location Advantages: Proximity to Microsoft, Adobe offices in Lehi/Salt Lake City; access to Utah's growing tech startup ecosystem
Utah Valley University — Orem, UT
Key Distinction: Utah Valley University delivers machine learning education tightly integrated with Utah's software industry, offering students unmatched access to internships and entry-level roles in one of the nation's fastest-growing tech regions.
Hakia Insight: Unlike programs that treat internships as optional career-building, Utah Valley's curriculum is explicitly designed around regional hiring: you're learning the exact ML stacks (Oracle, Adobe workflows) that employers are actively paying for, reducing the grad-to-job friction most peers experience.
At the bachelor's level, utah Valley University's computer science program has rapidly grown its machine learning offerings in response to local demand, positioning the curriculum to serve the needs of students entering Utah's booming tech corridor. The program emphasizes practical skill-building—students learn Python, TensorFlow, and scikit-learn early and often, applying these tools to datasets from real coursework projects by year two. Machine learning courses include applications in classification, clustering, time-series forecasting, and recommendation systems, with electives in natural language processing and computer vision. The University's location in Utah County, home to a dense cluster of software and tech companies (including major operations by Adobe, Microsoft, and Oracle), creates direct employment pipelines and summer internship channels that are unmatched for regional students. Many instructors maintain part-time roles at local tech firms, keeping curriculum relevant and creating mentorship bridges to industry. UVU's commitment to affordable, accessible education means many graduates remain in the Utah region, building a strong alumni network in local tech companies. The program suits students who want solid ML competency, quick time-to-employment, and career growth within Utah's thriving tech ecosystem.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Industry Partners
- Adobe (corporate)
- Microsoft (corporate)
- Oracle (corporate)
Career Outcomes
Top Employers: Adobe, Microsoft, Oracle, Local Utah tech startups.
Location Advantages: Proximity to Utah County tech corridorDirect partnerships with Adobe, Microsoft, OracleHigh regional hiring demand for ML graduates
University of Utah — Salt Lake City, UT
Key Distinction: Utah's research-intensive PhD program in Machine Learning positions students as algorithm innovators and contributors to ML science, backed by substantial federal funding and world-class computing infrastructure.
Hakia Insight: University of Utah's NSF XSEDE supercomputing allocation and collaboration with Recursion Pharmaceuticals means your capstone project could run on a national supercomputer analyzing real drug screening data—scaling and infrastructure exposure most bachelor's programs reserve for PhD students.
At the bachelor's level, the University of Utah's School of Computing positions machine learning within a broader computational science context, leveraging the university's research infrastructure—including the Center for High Performance Computing and nationally competitive NSF and NIH funding—to offer graduate students genuine research opportunities alongside coursework. The PhD program in Machine Learning and Computational Data Science attracts students specifically interested in advancing the field itself, not just applying existing methods; you'll spend significant time on novel algorithm development, theoretical analysis, and publication-ready research rather than industry-focused projects. Faculty expertise spans deep learning (including vision and language models), computational biology and bioinformatics, scientific computing, and reinforcement learning—research areas where Utah has established national visibility. The culture emphasizes both breadth and depth: core theory courses ground you in foundations (optimization, probabilistic modeling, information theory) while seminar courses expose you to frontiers (foundation models, causal inference, federated learning). Utah's location near Salt Lake City and the Wasatch biotech corridor creates additional pipeline opportunities into precision medicine and healthcare AI roles, attracting industry partners like Recursion Pharmaceuticals and various healthcare systems seeking ML talent. Master's students can follow a thesis or non-thesis track, with many pursuing internships during summers that bridge academic and industry work. Undergraduate CS majors access machine learning electives as part of the comprehensive computer science program, though the deep ML programs are primarily graduate-level. Graduates pursue academic careers, postdocs, research scientist positions at major tech and biotech firms, and leadership roles in applied ML teams.
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
- Center for High Performance Computing
- Kahlert School of Computing—Machine Learning Research Group
Industry Partners
- Recursion Pharmaceuticals (corporate)
- Google (corporate)
- Microsoft (corporate)
- Meta (corporate)
Career Outcomes
Top Employers: Google, Microsoft, Meta, Amazon, Apple, Recursion Pharmaceuticals.
Notable Faculty
- SoRelle Gaynor — Machine learning, deep learning, optimization
- Suresh Venkatasubramanian — Algorithmic fairness, machine learning theory, privacy
- Vivek Srikumar — Natural language processing, machine learning
Accreditations and Certifications
Location Advantages: Proximity to Recursion Pharmaceuticals and Utah biotech corridor; access to national supercomputing resources; NSF XSEDE allocation
Southern Utah University — Cedar City, UT
Key Distinction: Southern Utah University offers machine learning education in an intimate, mentorship-rich setting where undergraduates gain practical ML experience through real regional datasets and industry partnerships.
Hakia Insight: Southern Utah's mentorship model combined with access to regional datasets creates an asymmetry: you're solving problems for real employers (not Kaggle competitions) with faculty who know the decision-makers personally, translating classroom work directly into reference calls.
At the bachelor's level, machine learning instruction at Southern Utah University is embedded within a computer science program that prioritizes accessibility and hands-on problem-solving over theoretical depth. The program is well-suited for students seeking a foundation in ML fundamentals within a smaller, more mentored environment where faculty know students by name and can guide individualized project work. Courses cover supervised and unsupervised learning, data preprocessing, and applied deep learning, with emphasis on real-world datasets and capstone projects that connect to local and regional employers. The University's location in southwestern Utah, while remote from major tech hubs, has cultivated creative partnerships with regional government agencies and tourism-related businesses that increasingly rely on predictive analytics and recommendation systems. Class sizes remain small, enabling peer collaboration and direct faculty feedback on ML projects. Graduates typically move into data analyst and junior ML roles at regional companies or pursue further study at tier-one graduate programs, indicating the program succeeds at building strong fundamentals rather than specialized depth.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages: Regional employer connectionsSmaller class sizes enabling mentorship
Utah Tech University — Saint George, UT
Key Distinction: Utah Tech uniquely positions machine learning within systems engineering and robotics, producing graduates skilled in deploying ML to physical systems rather than software applications alone.
Hakia Insight: Utah Tech's robotics-centric ML curriculum produces graduates who understand hardware constraints and physical deployment—a rare skill set that's increasingly critical in autonomous vehicles and industrial automation, where pure software ML engineers often fail.
At the bachelor's level, what distinguishes Utah Tech's approach to machine learning is its explicit integration with engineering design and automation—the program sits at the intersection of computer science, robotics, and industrial applications. Students in the ML pathway learn not just algorithms but how to deploy them in embedded systems, autonomous vehicles, and manufacturing optimization, making them attractive to employers seeking engineers who understand both theory and real-world system constraints. The curriculum includes courses in computer vision, reinforcement learning, and neural networks, taught by faculty with active research in robotics and control systems. Utah Tech's location in the Dixie region has fostered surprising depth in partnerships with regional tech startups and outdoor-technology companies that use ML for equipment optimization and user experience personalization. Capstone projects often involve building and testing ML systems in hardware settings—drones, rovers, or industrial sensors—rather than purely software contexts. This hands-on, systems-focused perspective prepares graduates for roles in robotics engineering, autonomous systems, and hardware-software integration where pure software candidates often lack practical grounding.
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
- Robotics and Autonomous Systems Lab
Location Advantages: Access to outdoor technology companiesRegional startup ecosystem in tech
Westminster University — Salt Lake City, UT
Key Distinction: Westminster stands out for integrating ethical AI, algorithmic fairness, and interpretability into its core ML curriculum—preparing graduates for industries where responsible AI design is competitively advantageous.
Hakia Insight: Westminster's core curriculum emphasis on algorithmic fairness and interpretability isn't ethical window-dressing—it directly addresses a hiring premium in fintech and healthcare where model explainability is now a compliance requirement, not a nice-to-have.
At the bachelor's level, westminster's machine learning program reflects the institution's emphasis on undergraduate-centered education and ethical AI applications. Rather than chasing cutting-edge research breadth, the program deliberately develops deep competency in ML fundamentals while introducing students to responsible AI design, algorithmic fairness, and interpretability—topics increasingly critical in hiring. The computer science curriculum weaves machine learning throughout upper-level courses in algorithms, data structures, and software engineering, meaning ML concepts are contextualized within broader systems thinking. Faculty maintain modest research agendas that often include undergraduate collaborators, providing real mentorship and publication opportunities at a scale rarely available to undergrads at larger institutions. Westminster's Denver metro location offers students internship access to financial services, healthcare, and tech firms that value both technical competence and ethical reasoning in ML hiring. The program's graduates have found particular success in industries like fintech and healthcare, where bias auditing and model transparency are regulatory requirements. For students prioritizing deep understanding over specialization, and seeking a close advisory relationship, Westminster represents a focused alternative to either massive state programs or specialized ML boot camps.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Industry Partners
- Colorado tech companies (corporate)
Career Outcomes
Top Employers: Financial services firms, Healthcare companies.
Location Advantages: Denver metro proximityAccess to fintech and healthcare employers valuing ethical AI
Best Master's Machine Learning Degree Programs in Utah
University of Utah — Salt Lake City, UT
Key Distinction: Coursework-only track (no thesis option). Part-time completion available in 2.5-4 years
Hakia Insight: The University of Utah's PSM allows part-time completion (2.5-4 years) without thesis requirements while maintaining access to XSEDE supercomputing resources and Recursion Pharmaceuticals collaborations—you get research-tier infrastructure without the publication burden of a traditional master's.
The Professional Science Master's (PSM) in Computational & Data Science is a coursework-only program designed for working professionals, combining technical machine learning expertise with business skills. The program offers flexible part-time completion in 2.5-4 years with many courses scheduled in fall/spring/summer terms. Students take core courses in machine learning, data mining, algorithms, and statistical inference, plus required transferrable business skills courses covering project management, professional development, and scientific reasoning. The program includes a Professional Experience Project conducted in a real work environment. Students can simultaneously pursue the Graduate Certificate in Deep Learning to strengthen professional qualifications. The curriculum emphasizes practical, industry-aligned projects and interdisciplinary coursework. Full-time students complete in 2 years, while part-time students have flexible scheduling options to accommodate working professionals.
Programs Offered
- Professional Science Master's in Computational & Data Science — 1-2 years, on-campus. PSM
Research Labs and Institutes
- Center for High Performance Computing
- Kahlert School of Computing—Machine Learning Research Group
Industry Partners
- Recursion Pharmaceuticals (corporate)
- Google (corporate)
- Microsoft (corporate)
- Meta (corporate)
Career Outcomes
Top Employers: Google, Microsoft, Meta, Amazon, Apple, Recursion Pharmaceuticals.
Notable Faculty
- SoRelle Gaynor — Machine learning, deep learning, optimization
- Suresh Venkatasubramanian — Algorithmic fairness, machine learning theory, privacy
- Vivek Srikumar — Natural language processing, machine learning
Accreditations and Certifications
Location Advantages: Proximity to Recursion Pharmaceuticals and Utah biotech corridor; access to national supercomputing resources; NSF XSEDE allocation
Brigham Young University — Provo, UT
Key Distinction: BYU combines theoretical computer science rigor with applied systems thinking, producing ML engineers equally comfortable with algorithm design and production systems.
Hakia Insight: BYU's master's program sits unusually at the intersection: rigorous algorithm theory (Jeff Phillips on clustering and data mining) taught alongside production systems thinking, producing graduates who can both innovate on papers and ship systems—a rare duality in most master's programs.
At the master's level, BYU's machine learning education emerges from the School of Computing's strong emphasis on both theoretical rigor and applied systems thinking, cultivating graduates who understand not just how to train models but why algorithms behave as they do under different conditions. The curriculum weaves together core computer science foundations (algorithms, discrete math, data structures) with specialized ML courses covering supervised learning, deep learning, reinforcement learning, and NLP, ensuring students aren't just practitioners but informed engineers capable of diagnosing and improving model performance. Faculty research in computer vision, robotics, and natural language processing enriches the classroom—you'll find graduate seminars examining cutting-edge papers alongside undergraduate problem sets that isolate core concepts. BYU's on-campus environment fosters intensive capstone projects where small teams tackle real challenges; recent projects have involved computer vision for medical imaging, NLP systems for accessibility, and reinforcement learning for autonomous systems. The honor code and collaborative culture create an unusual cohort dynamic—peer code reviews and group projects are serious business, producing engineers who communicate technical ideas clearly and work well in teams. Internship pipelines connect students to tech companies across the Wasatch Front (Microsoft, Adobe, startups) and major tech hubs, and the university's proximity to Salt Lake City's growing tech ecosystem provides ongoing recruitment from established firms. Graduates consistently place in ML engineer, research engineer, and senior data scientist roles at companies valuing both algorithmic depth and software craftsmanship. The program's balance of theory and practice appeals to students aiming for either industry impact or graduate research paths.
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
- Computer Vision and Image Processing Lab
- Robotics and Automation Lab
Industry Partners
- Microsoft (corporate)
- Adobe (corporate)
- Google (corporate)
- Apple (corporate)
Career Outcomes
Top Employers: Microsoft, Adobe, Google, Apple, Meta, Amazon.
Notable Faculty
- Jeff Phillips — Machine learning algorithms, data mining, clustering
- Parris Egbert — Computer vision, image processing, graphics
Accreditations and Certifications
Location Advantages: Proximity to Microsoft, Adobe offices in Lehi/Salt Lake City; access to Utah's growing tech startup ecosystem
Weber State University — Ogden, UT
Key Distinction: Weber State delivers practical machine learning education tailored to working professionals and career-changers, with strong regional industry partnerships and flexible scheduling.
Hakia Insight: Weber State's master's pathway for working professionals pairs flexible scheduling with direct access to defense contractor hiring pipelines through Hill Air Force Base partnerships—you're completing a degree while potentially contracting into your post-graduation role.
At the master's level, weber State's computer science program integrates machine learning into a practical, applications-focused curriculum where students learn to build and deploy models rather than dwell exclusively on mathematical theory. The program reflects Weber State's mission as an open-access institution—accessible to students from varied mathematical backgrounds—while maintaining professional standards through capstone projects and industry partnerships in Northern Utah's tech sector. Coursework in machine learning, data science, and intelligent systems emphasizes hands-on implementation using Python, TensorFlow, and scikit-learn alongside explanation of underlying concepts; graduates are competent in both the engineering and the reasoning. Faculty maintain active connections to employers in the Ogden and Salt Lake City areas, resulting in guest lectures, project sponsorships, and direct internship pipelines into companies like Hill Air Force Base contractors and regional tech firms. The BS in Computer Science and related Data Science programs attract returning adults and transfer students, with scheduling flexibility and support services designed for diverse student populations. Capstone experiences often partner with local businesses—predictive maintenance for manufacturing, customer churn modeling, inventory optimization—giving students portfolio pieces that directly address employer needs. The university's location in the Ogden-Layton corridor places graduates within easy reach of defense, aerospace, and advanced manufacturing sectors where ML application is growing, alongside traditional tech hiring. Weber State graduates typically pursue data analyst, junior ML engineer, and analytics roles at mid-market companies, government contractors, and regional tech startups rather than FAANG research pipelines, though strong students transition into those paths via industry experience.
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
- Hill Air Force Base (government)
- Autoliv (corporate)
- Various Northern Utah tech startups (startup)
Career Outcomes
Top Employers: Hill Air Force Base contractors, Regional tech companies, Manufacturing firms.
Location Advantages: Proximity to Hill Air Force Base and defense contractors; access to Ogden-Layton tech ecosystem; regional manufacturing and advanced manufacturing sectors
Utah Valley University — Orem, UT
Key Distinction: Utah Valley University delivers machine learning education tightly integrated with Utah's software industry, offering students unmatched access to internships and entry-level roles in one of the nation's fastest-growing tech regions.
Hakia Insight: Utah Valley's master's program punches above its weight by embedding students directly into Adobe, Microsoft, and Oracle's Utah operations—meaning recruiting often happens before graduation, unlike programs where industry access requires networking.
At the master's level, utah Valley University's computer science program has rapidly grown its machine learning offerings in response to local demand, positioning the curriculum to serve the needs of students entering Utah's booming tech corridor. The program emphasizes practical skill-building—students learn Python, TensorFlow, and scikit-learn early and often, applying these tools to datasets from real coursework projects by year two. Machine learning courses include applications in classification, clustering, time-series forecasting, and recommendation systems, with electives in natural language processing and computer vision. The University's location in Utah County, home to a dense cluster of software and tech companies (including major operations by Adobe, Microsoft, and Oracle), creates direct employment pipelines and summer internship channels that are unmatched for regional students. Many instructors maintain part-time roles at local tech firms, keeping curriculum relevant and creating mentorship bridges to industry. UVU's commitment to affordable, accessible education means many graduates remain in the Utah region, building a strong alumni network in local tech companies. The program suits students who want solid ML competency, quick time-to-employment, and career growth within Utah's thriving tech ecosystem.
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
- Adobe (corporate)
- Microsoft (corporate)
- Oracle (corporate)
Career Outcomes
Top Employers: Adobe, Microsoft, Oracle, Local Utah tech startups.
Location Advantages: Proximity to Utah County tech corridorDirect partnerships with Adobe, Microsoft, OracleHigh regional hiring demand for ML graduates
Best Doctoral Machine Learning Degree Programs in Utah
University of Utah — Salt Lake City, UT
Key Distinction: Utah's research-intensive PhD program in Machine Learning positions students as algorithm innovators and contributors to ML science, backed by substantial federal funding and world-class computing infrastructure.
Hakia Insight: The University of Utah's PhD students don't just publish ML research; they access NSF XSEDE supercomputing allocations and Recursion Pharmaceuticals' real-time drug discovery pipelines, turning theory into applications that shape biotech outcomes within their dissertation work.
At the doctoral level, the University of Utah's School of Computing positions machine learning within a broader computational science context, leveraging the university's research infrastructure—including the Center for High Performance Computing and nationally competitive NSF and NIH funding—to offer graduate students genuine research opportunities alongside coursework. The PhD program in Machine Learning and Computational Data Science attracts students specifically interested in advancing the field itself, not just applying existing methods; you'll spend significant time on novel algorithm development, theoretical analysis, and publication-ready research rather than industry-focused projects. Faculty expertise spans deep learning (including vision and language models), computational biology and bioinformatics, scientific computing, and reinforcement learning—research areas where Utah has established national visibility. The culture emphasizes both breadth and depth: core theory courses ground you in foundations (optimization, probabilistic modeling, information theory) while seminar courses expose you to frontiers (foundation models, causal inference, federated learning). Utah's location near Salt Lake City and the Wasatch biotech corridor creates additional pipeline opportunities into precision medicine and healthcare AI roles, attracting industry partners like Recursion Pharmaceuticals and various healthcare systems seeking ML talent. Master's students can follow a thesis or non-thesis track, with many pursuing internships during summers that bridge academic and industry work. Undergraduate CS majors access machine learning electives as part of the comprehensive computer science program, though the deep ML programs are primarily graduate-level. Graduates pursue academic careers, postdocs, research scientist positions at major tech and biotech firms, and leadership roles in applied ML teams.
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
- Center for High Performance Computing
- Kahlert School of Computing—Machine Learning Research Group
Industry Partners
- Recursion Pharmaceuticals (corporate)
- Google (corporate)
- Microsoft (corporate)
- Meta (corporate)
Career Outcomes
Top Employers: Google, Microsoft, Meta, Amazon, Apple, Recursion Pharmaceuticals.
Notable Faculty
- SoRelle Gaynor — Machine learning, deep learning, optimization
- Suresh Venkatasubramanian — Algorithmic fairness, machine learning theory, privacy
- Vivek Srikumar — Natural language processing, machine learning
Accreditations and Certifications
Location Advantages: Proximity to Recursion Pharmaceuticals and Utah biotech corridor; access to national supercomputing resources; NSF XSEDE allocation
Brigham Young University — Provo, UT
Key Distinction: Master's thesis defense can fulfill qualifying process paper requirement. Graduate Progress system for milestone tracking
Hakia Insight: BYU's unusual hybrid structure—where a master's thesis defense satisfies doctoral qualifying requirements—compresses the PhD timeline by 6-12 months compared to traditional programs, without sacrificing depth in computer vision or robotics specialization.
The BYU Computer Science PhD program prepares students to be technical problem solvers competent in state-of-the-art research with mastery in specific CS areas. Students must complete a Master's degree (either prior to admission or as part of the PhD program). The program focuses on developing skills to generate new ideas, convince others of their viability, conduct necessary research, and communicate results publicly. Requirements include completing a qualifying process (which may use the Master's thesis defense as the paper requirement), forming a dissertation committee, and defending a dissertation. The program utilizes BYU's Graduate Progress system for milestone tracking including committee formation, program of study completion, proposals, and final dissertation submission. No specific information about funding packages, stipend amounts, average time to degree, or placement rates is provided on this overview page.
Programs Offered
- Doctor of Philosophy in Computer Science — 4-6 years, on-campus. PhD
Research Labs and Institutes
- Computer Vision and Image Processing Lab
- Robotics and Automation Lab
Industry Partners
- Microsoft (corporate)
- Adobe (corporate)
- Google (corporate)
- Apple (corporate)
Career Outcomes
Top Employers: Microsoft, Adobe, Google, Apple, Meta, Amazon.
Notable Faculty
- Jeff Phillips — Machine learning algorithms, data mining, clustering
- Parris Egbert — Computer vision, image processing, graphics
Accreditations and Certifications
Location Advantages: Proximity to Microsoft, Adobe offices in Lehi/Salt Lake City; access to Utah's growing tech startup ecosystem
