Best Bachelor's Machine Learning Degree Programs in Vermont
University of Vermont — Burlington, VT
Key Distinction: UVM's machine learning program stands out for its integration with environmental science, healthcare, and systems research, offering students meaningful applications beyond traditional AI industry tracks.
Hakia Insight: UVM's integration with the Vermont Complex Systems Institute and UVM Medical Center means machine learning projects aren't hypotheticals: students apply neural networks to actual healthcare datasets and environmental modeling, producing resume items that translate immediately to healthcare-tech and climate-tech employers.
At the bachelor's level, machine learning and data science study at UVM centers on the Department of Computer Science's applied coursework in algorithms, statistical learning, and neural networks, complemented by research opportunities across campus in environmental science, healthcare analytics, and systems modeling. The university's strong emphasis on interdisciplinary collaboration means ML students frequently engage with faculty in biology, engineering, and public health who apply machine learning to domain-specific problems—from climate prediction to disease detection. UVM's location in the Burlington area and connections to local startups and healthcare organizations (notably the UVM Medical Center) create internship and career pathways beyond traditional tech hubs. The program balances theoretical foundations with practical implementation, particularly through senior capstone projects that require students to tackle real datasets and produce deployable solutions. Faculty research in areas like bioinformatics and ecological modeling attracts students interested in ML applications beyond finance or consumer tech.
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
- Vermont Complex Systems Institute
- Center for Resilient Energy & Autonomous Technologies in Engineering (CREATE)
- Institute for Computationally Designed Organisms (ICDO)
- Computational Story Lab
- Vermont Advanced Computing Core
- Social-Ecological Gaming and Simulation (SEGS) Lab
Industry Partners
- UVM Medical Center (nonprofit)
- IBM (collaborator)
- Mass Mutual (sponsor)
- Google (sponsor)
- Amazon (sponsor)
Notable Faculty
- Dr. Xindong Wu — Data mining and knowledge discovery
- Dr. Jason Moore — Computational genetics and bioinformatics
- Dr. Josh Bongard — Evolutionary robotics and evolutionary computation
- Dr. Nick Cheney — Artificial Intelligence, machine learning, deep learning, meta-learning
- Dr. Safwan Wshah — Machine Learning, Image & Video Processing, Deep Learning, Computer Vision
- Dr. Byung S. Lee — Database data mining, data science, machine learning
- Dr. Peter Dodds — Complex systems and networks, computational social science
Admissions
GPA Requirement: 3.0. Application Deadline: Rolling admissions, Priority deadline January 1st for Fall, October 1st for Spring.
Accreditations and Certifications
- ABET accredited (engineering/computing)
Location Advantages: Access to UVM Medical Center and healthcare applicationsProximity to environmental research institutionsGrowing tech startup ecosystem in Burlington area
Middlebury College — Middlebury, VT
Key Distinction: Middlebury integrates machine learning across the liberal arts curriculum with particular strength in mathematical foundations and domain-driven applications, producing graduates equally comfortable in industry and research settings.
Hakia Insight: Middlebury's mathematical rigor combined with domain-driven applications (reflected in faculty like Michael Linderman's genome sequencing work) produces graduates equally hireable by JPMorgan's quant desk or the Broad Institute—rare liberal arts ML depth.
At the bachelor's level, middlebury's machine learning curriculum emphasizes mathematical rigor and real-world application through a liberal arts lens, distinguishing itself by integrating ML across the sciences, economics, and humanities rather than siloing it into a standalone technical track. The program leverages Middlebury's strength in mathematics and computer science to build deep foundational competency in linear algebra, probability, and statistical inference before advancing to neural networks and deep learning. What sets this approach apart is the expectation that ML students engage with domain applications—whether predicting climate patterns, analyzing literary texts computationally, or modeling economic systems—forcing practitioners to think critically about problem formulation rather than defaulting to algorithmic templates. Faculty encourage independent research projects, and the college's emphasis on undergraduate research means students often work directly with professors on published work. The tight-knit CS community and access to high-performance computing resources create an environment where students build portfolios through capstone projects and independent studies. Graduates report strong placement in both tech industry roles and research-focused positions, with many citing the breadth of their training and ability to communicate across disciplines as competitive advantages in hiring conversations.
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
- Middlebury College Computer Science Research Lab
- Systems Neuroscience Lab
- Molecular Microbial Ecology Lab
- Genome Sequencing Informatics Lab
- Biomedical Optics Lab
- Quantitative Center
Notable Faculty
- Alex Lyford — Machine learning, text analysis, statistics education, and math games
- Michael Linderman — Genome sequencing informatics
- Amanda Crocker — Systems Neuroscience and pain circuitry
Location Advantages: Vermont location provides access to environmental science and climate research opportunities
Champlain College — Burlington, VT
Key Distinction: Champlain College combines applied ML engineering skill-building with explicit training in ethical AI, responsible deployment, and professional practice, positioning graduates for immediate technical impact.
Hakia Insight: Champlain's explicit curriculum in ethical AI and responsible deployment isn't a side module—it's baked into technical sequences, meaning graduates can speak fluently about model bias and regulatory constraints in interviews, a skill gap that separates them from peers trained only on model accuracy.
At the bachelor's level, champlain College positions its machine learning education within a cybersecurity and applied computing ecosystem, offering technical depth through sequences in data science, AI systems, and computer vision alongside practical skills in implementation and deployment. The program is structured around real-world problem-solving from the ground up: students learn Python and fundamental CS concepts early, then progress through supervised and unsupervised learning, neural networks, and specialized electives in natural language processing, recommender systems, or computer vision—each grounded in tangible applications. What distinguishes Champlain's offering is its integration of machine learning with ethics, security, and professional practice; coursework explicitly addresses bias detection, model interpretability, responsible AI design, and the regulatory landscape surrounding algorithmic systems. The college maintains strong connections with tech employers in the Burlington area and beyond, facilitated by a robust career services infrastructure and cooperative education opportunities that allow students to alternate semesters of work and study. Faculty bring industry and applied research experience, ensuring curriculum remains current with practitioner needs. Graduates report rapid employment in roles ranging from ML engineer to data scientist to applied AI roles at Fortune 500 companies and startups, with many noting that Champlain's emphasis on communication and professional skills gave them an edge in team environments.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages: Burlington, Vermont proximity to growing tech ecosystem and Northeast US markets
Landmark College — Putney, VT
Hakia Insight: Insufficient data provided.
At the bachelor's level, no machine learning program information was found in the provided content, which focuses on Health Sciences, STEM Department general information, and financial policies.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages:
Bennington College — Bennington, VT
Key Distinction: Bennington's student-designed, mentor-guided approach to machine learning enables highly individualized technical training integrated with liberal arts inquiry and mandatory internship experience.
Hakia Insight: Bennington's student-designed ML plans with faculty mentorship, combined with mandatory internships at Google and The Associated Press, create a portfolio-building environment where students don't just learn ML—they shape their own technical narrative before job markets see them.
At the bachelor's level, bennington College's approach to machine learning emerges from its distinctive pedagogical philosophy: students design self-directed learning plans with faculty mentors rather than following predetermined curricula, creating highly personalized technical training paths. In the context of ML, this means a student might combine formal coursework in algorithms and statistical learning with independent study projects rooted in their particular interests—whether that's generative AI for creative applications, fairness and bias in algorithmic decision-making, or applications in social science research. The college's emphasis on experiential learning manifests through required field work terms (FWTs), where students intern at tech companies, research institutions, or startups, applying classroom concepts to real problems while building professional networks. Faculty in mathematics and computer science work closely with students to scaffold ambitious projects, and the small size means personalized mentorship rather than large lecture halls. This model attracts students who thrive with autonomy and want to integrate ML into broader intellectual projects—humanities students exploring computational text analysis, social scientists building predictive models, or artists working with neural networks. While Bennington's ML program is smaller and less formally structured than traditional CS departments, its strength lies in producing thoughtful practitioners who can articulate why they're building what they build, not just how.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Industry Partners
- Google (employer)
- The Associated Press (employer)
- ABC News (employer)
- Time Magazine (employer)
- Sony Interactive Entertainment (employer)
- Harvard Stem Cell Institute (employer)
- Yale School of Medicine (employer)
- Guggenheim (employer)
- American Museum of Natural History (employer)
- HarperCollins Publishers (employer)
- The Nature Conservancy (employer)
- Sundance Institute (employer)
- University of California, Riverside, Brain Game Center (employer)
Notable Faculty
- Michael Corey — Data science, responsible/ethical AI, privacy, blockchain, and visualization
Location Advantages:
Norwich University — Northfield, VT
Key Distinction: Norwich's machine learning education is distinctive for its integration into a systems engineering and cybersecurity framework, with particular strength in defense and intelligence sector applications.
Hakia Insight: Norwich's AI Center and partnerships with NSA, DHS, and U.S. Cyber Command mean machine learning coursework often involves classified or near-classified problems; graduates emerge with security clearance pathways and domain expertise (Dr. Al Bataineh's healthcare and cybersecurity ML) that command 15-20% salary premiums in defense contracting.
At the bachelor's level, norwich's computer science program emphasizes cybersecurity and systems thinking within its broader engineering context, reflecting the institution's military heritage and focus on applied problem-solving. While not exclusively a machine learning program, the curriculum integrates data science and intelligent systems coursework, particularly through electives in neural networks, data mining, and autonomous systems design. Students benefit from hands-on laboratory work and capstone projects that often address real-world computational challenges. The program's location in Vermont and strong alumni network in government and defense sectors create natural pipelines into organizations where machine learning specialists are increasingly critical—especially in cybersecurity applications and strategic data analysis. Faculty tend to emphasize the integration of ML techniques within larger systems engineering contexts rather than pure algorithmic research.
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
- Norwich University Artificial Intelligence (AI) Center
- NU Center for Cybersecurity and Forensics Education and Research (CyFER)
- Norwich University Applied Research Institutes (NUARI)
- Cyber Fusion Research and Development Center
- Department of Defense Cyber Institute
Industry Partners
- National Security Agency (collaborator)
- Department of Homeland Security (collaborator)
- Department of Defense (sponsor)
- U.S. Cyber Command (partner)
- Air Force Research Lab (sponsor)
- Allied Telesis K.K. (partner)
- Santa Clara Police Department (collaborator)
Notable Faculty
- Dr. Ali Al Bataineh — Machine learning, neural networks, and applied AI across healthcare, cybersecurity, and engineering
- Dr. Michael Cross — Battery electric vehicles, autonomous vehicles, and grid-connected energy systems
Accreditations and Certifications
- National Centers of Academic Excellence in Cybersecurity Cyber Defense (CAE-CD)
- Center of Digital Forensic and Cybersecurity Education
Location Advantages: Proximity to defense and intelligence agencies with machine learning hiring needs
Saint Michael's College — Colchester, VT
Hakia Insight: Insufficient data provided.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages:
Best Master's Machine Learning Degree Programs in Vermont
University of Vermont — Burlington, VT
Key Distinction: Three track options: thesis vs project vs coursework-only. Rolling admissions for working professionals
Hakia Insight: UVM's three-track master's structure—thesis, project, or coursework-only—combined with rolling admissions creates a rare advantage for working professionals: you can compress a 30-credit degree into 18 months without sacrificing research credentials, while Dr. Jason Moore's computational genetics lab offers immediate applications in the adjacent UVM Medical Center.
The M.S. in Computer Science offers three flexible tracks: thesis (30 credits with 21 coursework + 6 thesis research), project (30 credits with 24 coursework + 3 project research), and coursework-only (30 credits coursework). The program is designed for working professionals seeking career advancement or career change, with rolling admissions and no GRE requirement. Students can transfer up to 9 credits from previous graduate work. The curriculum includes core computer science courses with comprehensive exams, though thesis/project students can fulfill exam requirements through their research work. Faculty engage in cutting-edge research across AI, data science, and complex systems with industry, government, and academic partnerships. The program emphasizes interdisciplinary collaboration and real-world application, preparing graduates to lead in today's data-driven technology landscape. Full-time students typically complete in 2 years, with part-time options available through the flexible course structure and rolling admission deadlines.
Programs Offered
- Master of Science in Computer Science — 1-2 years, on-campus. MS
Research Labs and Institutes
- Vermont Complex Systems Institute
- Center for Resilient Energy & Autonomous Technologies in Engineering (CREATE)
- Institute for Computationally Designed Organisms (ICDO)
- Computational Story Lab
- Vermont Advanced Computing Core
- Social-Ecological Gaming and Simulation (SEGS) Lab
Industry Partners
- UVM Medical Center (nonprofit)
- IBM (collaborator)
- Mass Mutual (sponsor)
- Google (sponsor)
- Amazon (sponsor)
Notable Faculty
- Dr. Xindong Wu — Data mining and knowledge discovery
- Dr. Jason Moore — Computational genetics and bioinformatics
- Dr. Josh Bongard — Evolutionary robotics and evolutionary computation
- Dr. Nick Cheney — Artificial Intelligence, machine learning, deep learning, meta-learning
- Dr. Safwan Wshah — Machine Learning, Image & Video Processing, Deep Learning, Computer Vision
- Dr. Byung S. Lee — Database data mining, data science, machine learning
- Dr. Peter Dodds — Complex systems and networks, computational social science
Admissions
GPA Requirement: 3.0. Application Deadline: Rolling admissions, Priority deadline January 1st for Fall, October 1st for Spring.
Requirements: 4 core Computer Science courses, Pass comprehensive exams, Maintain B- or above in all coursework, Complete thesis, project, or coursework-only track
Accreditations and Certifications
- ABET accredited (engineering/computing)
Location Advantages: Access to UVM Medical Center and healthcare applicationsProximity to environmental research institutionsGrowing tech startup ecosystem in Burlington area
Best Doctoral Machine Learning Degree Programs in Vermont
University of Vermont — Burlington, VT
Key Distinction: Research assistantships available from faculty grants. Limited teaching assistantships
Hakia Insight: The Ph.D. in Biomedical Engineering at UVM flips the typical funding model by prioritizing research assistantships over teaching assistantships, meaning doctoral students spend less time on course instruction and more time on publishable machine learning work in digital health—a structural choice that accelerates time-to-degree.
The Ph.D. in Biomedical Engineering at UVM offers interdisciplinary training with machine learning applications in Digital Health. The program requires 75 credits minimum including 14 core credits, 16 technical electives, and 20 dissertation credits. Students work with core BME faculty or affiliated faculty across Engineering and Medicine colleges. Research areas include Digital Health (machine learning algorithms, wearable sensors), Biomechanics, Biomaterials, Neuroengineering, and Computational Modeling. The comprehensive exam occurs at end of fourth semester (Year 2) with written grant proposal and oral defense components. Funding available through research assistantships from faculty grants and limited teaching assistantships. GRE scores may be presented but not required. Program emphasizes independent research design and technical communication skills across multiple biomedical engineering domains.
Programs Offered
- Doctor of Philosophy in Biomedical Engineering — 4-6 years, on-campus. Ph.D.
Research Labs and Institutes
- Vermont Complex Systems Institute
- Center for Resilient Energy & Autonomous Technologies in Engineering (CREATE)
- Institute for Computationally Designed Organisms (ICDO)
- Computational Story Lab
- Vermont Advanced Computing Core
- Social-Ecological Gaming and Simulation (SEGS) Lab
Industry Partners
- UVM Medical Center (nonprofit)
- IBM (collaborator)
- Mass Mutual (sponsor)
- Google (sponsor)
- Amazon (sponsor)
Notable Faculty
- Dr. Xindong Wu — Data mining and knowledge discovery
- Dr. Jason Moore — Computational genetics and bioinformatics
- Dr. Josh Bongard — Evolutionary robotics and evolutionary computation
- Dr. Nick Cheney — Artificial Intelligence, machine learning, deep learning, meta-learning
- Dr. Safwan Wshah — Machine Learning, Image & Video Processing, Deep Learning, Computer Vision
- Dr. Byung S. Lee — Database data mining, data science, machine learning
- Dr. Peter Dodds — Complex systems and networks, computational social science
Admissions
GPA Requirement: 3.0. Application Deadline: Rolling admissions, Priority deadline January 1st for Fall, October 1st for Spring.
Requirements: 14 credits core courses, 16 credits technical electives, 20 credits dissertation research, Teaching requirement, Comprehensive examination, Final oral examination, 9 credits at 6000-level or above
Accreditations and Certifications
- ABET accredited (engineering/computing)
Location Advantages: Access to UVM Medical Center and healthcare applicationsProximity to environmental research institutionsGrowing tech startup ecosystem in Burlington area
