Best Bachelor's Machine Learning Degree Programs in Tennessee
Vanderbilt University — Nashville, TN
Key Distinction: Vanderbilt's machine learning program stands out for its integrated healthcare AI research pipeline and medical center partnerships, rare among peer institutions.
Hakia Insight: Vanderbilt's proximity to its own medical center creates an rare undergraduate advantage: students don't study healthcare AI in theory—faculty like Yaoyu Cheng actively deploy models in hospital imaging labs, meaning capstone projects have direct clinical relevance that peers at Georgia Tech or UT Austin cannot replicate.
At the bachelor's level, vanderbilt's machine learning offerings emerge from a strong electrical engineering and computer science foundation, with particular depth in deep learning, computer vision, and natural language processing. The program benefits from the institution's research intensity and Nashville's growing tech ecosystem. Faculty-led research groups tackle applications spanning healthcare AI, autonomous systems, and speech processing, creating pipelines for students to move directly into research roles. The computer science curriculum emphasizes both theoretical rigor and practical implementation, with courses in neural networks, probabilistic graphical models, and reinforcement learning. Graduate students frequently collaborate with faculty on published research, and the proximity to Vanderbilt Medical Center opens unique opportunities in healthcare AI and biomedical signal processing. Career outcomes are strong, with graduates placed at major tech firms, startups, and research institutions. The program's strength lies in balancing academic depth with applied research exposure—students aren't just learning ML theory in isolation but engaging with real problems in healthcare, robotics, and data science from day one.
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
- Vanderbilt Institute for Software Integrated Systems (ISIS)
- Learning and Reasoning Lab
Industry Partners
- HCA Healthcare (corporate)
- Amazon (corporate)
- Google (corporate)
Career Outcomes
Top Employers: Google, Amazon, Microsoft, Meta.
Notable Faculty
- Yaoyu Cheng — Machine learning in medical imaging and healthcare AI
- Gabor Karsai — Embedded systems and cyber-physical systems with machine learning
Accreditations and Certifications
- ABET accredited (engineering programs)
Location Advantages: Nashville tech ecosystem growthProximity to Vanderbilt Medical Center for healthcare AI applicationsRegional hub for healthcare and financial services companies
The University of Tennessee-Knoxville — Knoxville, TN
Key Distinction: UTK's machine learning program is uniquely positioned through direct Oak Ridge National Laboratory partnerships, offering rare access to supercomputing infrastructure for student and faculty research.
Hakia Insight: UTK's Oak Ridge partnership isn't just a recruiting talking point—undergraduates can access Summit and Frontier supercomputers for thesis work, infrastructure most PhD programs at peer institutions gatekeep, giving students a computational scale advantage that translates directly to distributed systems expertise.
At the bachelor's level, machine learning education at UTK benefits from the university's significant strengths in high-performance computing and data-intensive science. The computer science program has developed specialized tracks in machine learning and artificial intelligence that leverage the institution's Oak Ridge National Laboratory partnerships—a rare advantage for undergraduates and graduate students alike. Students gain hands-on exposure to large-scale computing infrastructure and real-world ML applications in materials science, energy systems, and computational biology. The curriculum balances theoretical foundations with immediate research application, and many students participate in projects using ORNL's supercomputing resources. Faculty expertise spans deep learning, graph neural networks, and domain-specific applications in scientific computing. The program's distinctive character comes from this research-driven approach paired with access to world-class computing facilities; students leave with not just ML skills but experience scaling algorithms to massive datasets. Career placement is strong across tech companies and national laboratories, with many graduates leveraging their HPC background in roles requiring computational sophistication.
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
- Institute for Advanced Computational Science
- Innovative Computing Laboratory (ICL)
Industry Partners
- Oak Ridge National Laboratory (government)
- NVIDIA (corporate)
- IBM (corporate)
Career Outcomes
Top Employers: Oak Ridge National Laboratory, IBM, NVIDIA, Intel, Google.
Notable Faculty
- Stanimire Tomov — GPU-accelerated machine learning, linear algebra software
- Jiajia Li — Distributed machine learning, high-performance computing
Admissions
GPA Requirement: 3.0 (3.3 for international students). Application Deadline: January 15 (priority deadline).
Accreditations and Certifications
Location Advantages: Oak Ridge National Laboratory partnership and proximityAccess to supercomputing infrastructure (Summit, Frontier)Regional hub for scientific computing and energy research
Tennessee Technological University — Cookeville, TN
Key Distinction: TTU's machine learning program is distinctive for its systems engineering perspective, emphasizing embedded ML and control applications rather than pure data science.
Hakia Insight: While peer programs chase data science prestige, Tennessee Tech's embedded ML and control systems focus feeds directly into the Nissan manufacturing ecosystem 30 minutes away, positioning graduates for roles competitors categorize as 'robotics engineering' but with machine learning as the core skill.
At the bachelor's level, tennessee Tech's machine learning program emphasizes practical engineering applications and real-world problem solving within a strong electrical and computer engineering context. The curriculum centers on applied machine learning for control systems, signal processing, and industrial automation—areas where the region's manufacturing and engineering sectors are actively recruiting. Students work on hands-on capstone projects deploying ML models in predictive maintenance, embedded systems, and autonomous vehicles. The program integrates circuit design, signal processing fundamentals, and modern deep learning techniques, giving graduates a rare combination of hardware understanding and ML expertise. Faculty research often bridges the gap between traditional controls engineering and contemporary neural network approaches, creating a distinctive angle for students interested in robotics, IoT, and smart systems. The institution's strong industry ties in Tennessee manufacturing and automotive sectors create direct pathways to employment. Career outcomes reflect this specialization: graduates excel in roles requiring both ML competency and systems-level thinking, particularly in companies building intelligent physical systems rather than pure software platforms.
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
- Electrical and Computer Engineering Research Center
Industry Partners
- Nissan North America (corporate)
- Denso (corporate)
Career Outcomes
Top Employers: Nissan, Denso, General Motors, Booz Allen Hamilton.
Accreditations and Certifications
Location Advantages: Proximity to automotive manufacturing hub (Nissan plant)Strong regional manufacturing and industrial baseCentral Tennessee location with access to Nashville tech ecosystem
Middle Tennessee State University — Murfreesboro, TN
Key Distinction: MTSU's machine learning program prioritizes accessibility and interdisciplinary application, building competent practitioners from diverse backgrounds and equipping them for roles across industries beyond tech.
Hakia Insight: MTSU's explicit welcome of non-traditional technical backgrounds, paired with partnerships spanning St. Jude's Children's Hospital to the NSF I-Corps network, produces graduates positioned for healthcare and startup ML roles that require cross-functional communication—a scarcity among CS-heavy competitors.
At the bachelor's level, MTSU's approach to machine learning education centers on accessibility and breadth—the program welcomes students from diverse technical backgrounds and builds them into competent practitioners through incremental skill development. Rather than assuming advanced mathematics prerequisites, the curriculum scaffolds students from fundamentals through advanced topics, covering data preprocessing, feature engineering, supervised and unsupervised learning, and deep learning architectures. The program stands out for its flexibility: students can pursue machine learning as a concentration within computer science, data science, or engineering programs, allowing customization based on career goals. MTSU emphasizes interdisciplinary applications, encouraging students to apply machine learning to problems in education, healthcare, business analytics, and social sciences—not just pure computer science domains. Lab work is woven throughout, with access to modern computing resources and cloud platforms for training and deploying models. Faculty expertise spans machine learning systems, optimization, and applications in real-world domains. The university's location in Murfreesboro, near Nashville's growing tech corridor, offers internship and networking opportunities with companies increasingly relocating to Middle Tennessee. MTSU graduates enter roles ranging from junior data analysts to machine learning engineers, many reporting strong salary growth within 2–3 years of graduation. The program also supports students pursuing further education, with strong preparation for PhD programs in machine learning and related 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
- QRISE Center
- Undergraduate Research Center
Industry Partners
- St. Jude's Children's Hospital (employer)
- Oak Ridge National Laboratory (employer)
- Vanderbilt Wond'ry (sponsor)
- NSF I-Corps (sponsor)
Notable Faculty
- Dr. John Wallin — Computational and Data Science Program Director
- Dr. Misa Faezipour — Health systems engineering using machine learning and optimization
- Dr. Lei Miao — Reinforcement learning for intelligent transportation systems and wireless networks
- Dr. Jorge Vargas — Autonomous vehicle sensor systems and hardware-in-the-loop testing
Location Advantages: Proximity to Nashville's tech and fintech growthAccess to Tennessee innovation and entrepreneurship networks
The University of Tennessee-Chattanooga — Chattanooga, TN
Key Distinction: UTC combines rigorous machine learning fundamentals with embedded industry partnerships and applied projects in manufacturing and industrial AI, creating a practical pipeline to careers in data science and AI engineering.
Hakia Insight: UTC's industrial AI focus and TVA partnership position students for a specific career ladder most programs ignore: manufacturing-adjacent ML roles (predictive maintenance, supply chain optimization) where salaries approach software engineering but competition for talent remains regional rather than global.
UTC's machine learning program emphasizes practical application through project-based learning and industry collaboration, positioning students to transition directly into data science and AI roles. The curriculum balances theoretical foundations in algorithms, statistics, and neural networks with hands-on experience in Python, TensorFlow, and cloud platforms. What sets this program apart is its integration with Chattanooga's growing tech ecosystem—students gain real-world exposure through capstone projects with local companies and partner organizations. The program particularly shines in applied machine learning for manufacturing and industrial systems, reflecting the region's economic focus. Faculty bring research experience in computer vision, natural language processing, and predictive analytics, ensuring coursework stays current with industry trends. Graduates frequently move into machine learning engineer, data scientist, and AI specialist roles at companies ranging from Fortune 500 firms to innovative startups. The smaller cohort size means stronger mentorship and more opportunities for individual research projects. UTC's location in Chattanooga—increasingly recognized as a tech talent hub—provides networking advantages and internship pipelines that many students leverage into full-time positions before graduation. Whether pursuing a bachelor's or master's degree, students benefit from faculty who actively consult with industry, bringing real problems and emerging techniques directly into the classroom.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages: Chattanooga's emerging tech hub statusRegional manufacturing and industrial AI demandAccess to Tennessee Valley Authority (TVA) innovation initiatives
The University of the South — Sewanee, TN
Key Distinction: The University of the South offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: The University of the South's limited data prevents detailed competitive positioning at this time; prospective students should request specific curriculum, employer placement data, and faculty research areas directly from the institution to evaluate against peers with transparent outcomes.
The University of the South offers Machine Learning programs in Sewanee, TN. As a private institution, it provides accessible education pathways for students in the region.
University of Memphis — Memphis, TN
Key Distinction: Memphis distinguishes itself through active research partnerships with Fortune 500 logistics and healthcare companies, combined with faculty expertise in scalable ML systems and applied AI deployment.
Hakia Insight: Memphis graduates entering FedEx and its ecosystem gain access to supply chain and logistics datasets that academic programs cannot simulate—students co-author papers on 100-million-package problems, a research pedigree that distinguishes them from graduates trained on Kaggle datasets.
At the bachelor's level, the University of Memphis machine learning program leverages the institution's research strengths in data science and computational methods, with a curriculum that balances mathematical foundations with contemporary AI applications. The program emphasizes statistical learning theory, optimization algorithms, and scalable machine learning systems, preparing students for roles in both research and industry settings. Memphis has developed partnerships with regional healthcare systems and logistics companies—particularly FedEx, headquartered in the city—creating internship and research opportunities in real-world ML deployment. The graduate program attracts students seeking rigorous training in deep learning, reinforcement learning, and machine vision, often paired with domain expertise in healthcare informatics or supply chain optimization. Faculty research groups actively pursue NSF-funded projects in machine learning applications, giving graduate students access to funded research positions. Memphis's location in a major logistics and healthcare hub provides direct access to companies deploying machine learning at scale, and many graduates transition into senior data science and research engineer roles at these organizations or tech firms nationwide.
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
- Computational Intelligence Laboratory
- NIH mDOT Center
- MD2K Center of Excellence
- Center for Information Assurance
- Center for Disaster Recovery and Resiliency
- Electroptics and Remote Sensors Laboratory
- Autonomous & Complex Systems Laboratory
Industry Partners
- FedEx (corporate)
- FedEx Institute of Technology (sponsor)
- Defense Human Resources Activity (sponsor)
- Department of Defense (sponsor)
- US Department of Transportation (sponsor)
- US Department of Labor (sponsor)
- City of Memphis (collaborator)
Career Outcomes
Top Employers: FedEx, Healthcare systems in the Mid-South.
Notable Faculty
- Dr. Deepak Venugopal — Machine learning and artificial intelligence
- Dr. Santosh Kumar — Artificial intelligence for wearables and mobile sensor big data
- Dr. Dipankar Dasgupta — Bio-inspired computing, cybersecurity, trustworthy AI
- Dr. Bonny Banerjee — Computational Intelligence, machine learning, cognitive science
- Dr. Xiaolei Huang — Natural language processing and machine learning
- Dr. Haomiao Ni — Computer vision, machine learning, artificial intelligence
- Dr. Kan Yang — Adversarial machine learning and data security
Location Advantages: FedEx headquarters presenceMajor healthcare and medical research institutionsCentral logistics and supply chain industry hub
Rhodes College — Memphis, TN
Key Distinction: Rhodes College offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: The limited data available for Rhodes College prevents a substantive competitive analysis; prospective students should request detailed curriculum, research lab participation opportunities, employer partnerships, and recent graduate placement outcomes to meaningfully compare against peers with transparent metrics.
Rhodes College offers Machine Learning programs in Memphis, TN. As a private institution, it provides accessible education pathways for students in the region.
Tennessee State University — Nashville, TN
Key Distinction: TSU embeds machine learning education within a historically Black university context that emphasizes responsible AI development and equity considerations alongside technical depth.
Hakia Insight: TSU's framing of responsible AI and equity within ML education—rare among peer bachelor's programs—attracts students and faculty committed to bias auditing and fairness; this institutional emphasis translates to capstones addressing algorithmic discrimination, a skillset increasingly demanded by compliance-conscious enterprises.
At the bachelor's level, as a historically Black university with significant research infrastructure, Tennessee State University's machine learning offerings reflect institutional strengths in applied computing and data science with particular attention to equitable access and representation in technical fields. The program leverages TSU's research centers and collaborative partnerships to engage students in substantive machine learning projects that contribute to published work and real-world problem-solving. Students gain experience with industrial-scale tools and methodologies through partnerships with technology companies and research initiatives, providing exposure to how machine learning operates in production systems rather than solely in academic settings. Faculty expertise spans multiple specializations—from computer vision and natural language processing to reinforcement learning and time-series analysis—allowing students to pursue depth in areas aligned with their career interests. The curriculum emphasizes mathematical foundations alongside practical implementation, ensuring graduates understand both the theoretical underpinnings and the engineering practices that successful practitioners need. Distinctive to TSU is its commitment to broadening participation in AI and machine learning fields; the program actively supports students from underrepresented backgrounds and creates mentoring networks that extend into industry. Students participate in research groups, attend technical conferences, and engage with internship opportunities at major technology firms and research institutions. The combination of rigorous technical training, research participation, and institutional commitment to diversity prepares graduates for leadership roles in machine learning and data science while contributing to a field that historically has lacked representation from Black technologists and researchers.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages: Access to Nashville's tech corridor and healthcare sector companies
Lipscomb University — Nashville, TN
Key Distinction: Lipscomb integrates technical machine learning rigor with explicit focus on ethical AI and responsible deployment, grounded in the university's values-centered educational philosophy.
Hakia Insight: Lipscomb's values-centered ethical AI curriculum is not a humanities add-on but embedded in technical courses—graduates enter roles at healthcare and fintech companies already fluent in governance questions (model interpretability, bias mitigation, regulatory compliance) that most hires must learn on the job.
At the bachelor's level, lipscomb's machine learning coursework emphasizes practical application within a computationally rigorous framework, where students build real-world projects alongside theoretical foundations in supervised and unsupervised learning. The program integrates machine learning across the computer science curriculum rather than isolating it as a separate track, meaning you'll encounter ML concepts in algorithms, databases, and software engineering courses—a breadth-first approach that develops flexibility in how you apply these tools across domains. Faculty prioritize mentorship on capstone projects where students deploy models in healthcare, business analytics, and educational technology contexts, reflecting Nashville's growing biotech and healthcare IT sectors. The relatively intimate class sizes at Lipscomb mean you're not a number in a 300-person lecture; you have direct access to instructors who can guide your specialization interests, whether that's computer vision, NLP, or reinforcement learning. Graduates report strong placement in regional tech companies and healthcare firms, with several pursuing advanced degrees at tier-one institutions. The program benefits from Lipscomb's location in Nashville's expanding tech corridor and partnerships with local healthcare providers who actively recruit for data science roles.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages: Nashville's expanding healthcare IT and biotech sectorRegional tech company recruitment pipeline
Best Master's Machine Learning Degree Programs in Tennessee
Vanderbilt University — Nashville, TN
Key Distinction: Vanderbilt's machine learning program stands out for its integrated healthcare AI research pipeline and medical center partnerships, rare among peer institutions.
Hakia Insight: Vanderbilt's master's program capitalizes on faculty like Cheng actively shipping healthcare AI into HCA's patient-facing systems; thesis projects with clinical deployment potential create a hiring signal that distinguishes Vanderbilt graduates from graduates of larger, more anonymous programs.
At the master's level, vanderbilt's machine learning offerings emerge from a strong electrical engineering and computer science foundation, with particular depth in deep learning, computer vision, and natural language processing. The program benefits from the institution's research intensity and Nashville's growing tech ecosystem. Faculty-led research groups tackle applications spanning healthcare AI, autonomous systems, and speech processing, creating pipelines for students to move directly into research roles. The computer science curriculum emphasizes both theoretical rigor and practical implementation, with courses in neural networks, probabilistic graphical models, and reinforcement learning. Graduate students frequently collaborate with faculty on published research, and the proximity to Vanderbilt Medical Center opens unique opportunities in healthcare AI and biomedical signal processing. Career outcomes are strong, with graduates placed at major tech firms, startups, and research institutions. The program's strength lies in balancing academic depth with applied research exposure—students aren't just learning ML theory in isolation but engaging with real problems in healthcare, robotics, and data science from day one.
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
- Vanderbilt Institute for Software Integrated Systems (ISIS)
- Learning and Reasoning Lab
Industry Partners
- HCA Healthcare (corporate)
- Amazon (corporate)
- Google (corporate)
Career Outcomes
Top Employers: Google, Amazon, Microsoft, Meta.
Notable Faculty
- Yaoyu Cheng — Machine learning in medical imaging and healthcare AI
- Gabor Karsai — Embedded systems and cyber-physical systems with machine learning
Accreditations and Certifications
- ABET accredited (engineering programs)
Location Advantages: Nashville tech ecosystem growthProximity to Vanderbilt Medical Center for healthcare AI applicationsRegional hub for healthcare and financial services companies
Middle Tennessee State University — Murfreesboro, TN
Key Distinction: Online and on-campus course options available. Flexible scheduling for working professionals
Hakia Insight: MTSU's online master's option at a state school price point, combined with St. Jude's and Oak Ridge partnerships, creates an unusual value proposition for working professionals in healthcare and scientific computing who need credentials without leaving Tennessee—a market position neither elite private universities nor fully-online competitors fill.
MTSU's Master of Science in Data Science prepares working professionals for competitive careers in the rapidly growing data science field, ranked as one of the best careers. The program offers both online and on-campus courses, allowing full-time students and working professionals to find suitable paths toward their degree. Students gain advanced skills in computer programming, data visualization and manipulation, predictive modeling, business analytics, and communications. The curriculum is designed with flexibility - students can work with the program director to maximize or minimize online courses according to their needs and preferences. Through the Data Science Institute, students have opportunities to work on compensated data projects with companies, research projects with faculty, and data projects helping nonprofits. The program also offers Data Dives (hackathons) where students analyze real company or nonprofit data in 24-36 hour events. Graduates are prepared for roles at notable companies including Amazon, Deloitte, Nissan, HCA, and many others in Nashville's $7.5 billion technology industry.
Programs Offered
- Master of Science in Data Science — 1-2 years, on-campus. MS
Research Labs and Institutes
- QRISE Center
- Undergraduate Research Center
Industry Partners
- St. Jude's Children's Hospital (employer)
- Oak Ridge National Laboratory (employer)
- Vanderbilt Wond'ry (sponsor)
- NSF I-Corps (sponsor)
Career Outcomes
Top Employers: Amazon, Intel.
Notable Faculty
- Dr. John Wallin — Computational and Data Science Program Director
- Dr. Misa Faezipour — Health systems engineering using machine learning and optimization
- Dr. Lei Miao — Reinforcement learning for intelligent transportation systems and wireless networks
- Dr. Jorge Vargas — Autonomous vehicle sensor systems and hardware-in-the-loop testing
Location Advantages: Proximity to Nashville's tech and fintech growthAccess to Tennessee innovation and entrepreneurship networks
The University of Tennessee-Knoxville — Knoxville, TN
Key Distinction: Fully online asynchronous format with some synchronous components. Year-round course offerings including summer terms for acceleration
Hakia Insight: UT-Knoxville's proximity to Oak Ridge National Laboratory and direct access to Summit and Frontier supercomputers means students aren't just learning ML theory—they're writing code on machines that rank among the world's fastest, a computational advantage most universities simulate rather than provide.
The University of Tennessee-Knoxville's online Master of Science in Computer Science is a 30-credit, fully online program designed for working STEM professionals. Students can complete the degree in 18-24 months through asynchronous coursework offered year-round including summers, allowing for accelerated progress. The program offers three specialized concentrations: Cybersecurity, Data Mining and Intelligent Systems, or Software Engineering. Students learn advanced computer science concepts including machine learning, artificial intelligence, software security, and cloud computing from faculty including White House policy leaders and NSF researchers. The mixed format combines asynchronous and synchronous components to accommodate working professionals' schedules. Graduates develop specialized skills in high-demand areas like deep learning and software engineering, positioning them for leadership roles in a rapidly expanding field with significant earning potential. The program is offered by a top-ranked public engineering school and provides the advanced technical knowledge needed for specialized computer science roles that require skills beyond general degrees.
Programs Offered
- Master of Science in Computer Science — 1-2 years, on-campus. MS
Research Labs and Institutes
- Institute for Advanced Computational Science
- Innovative Computing Laboratory (ICL)
Industry Partners
- Oak Ridge National Laboratory (government)
- NVIDIA (corporate)
- IBM (corporate)
Notable Faculty
- Stanimire Tomov — GPU-accelerated machine learning, linear algebra software
- Jiajia Li — Distributed machine learning, high-performance computing
Admissions
GPA Requirement: 3.0 (3.3 for international students). Application Deadline: January 15 (priority deadline).
Requirements: Complete 30 credit hours, Maintain program requirements
Accreditations and Certifications
Location Advantages: Oak Ridge National Laboratory partnership and proximityAccess to supercomputing infrastructure (Summit, Frontier)Regional hub for scientific computing and energy research
Tennessee Technological University — Cookeville, TN
Key Distinction: TTU's machine learning program is distinctive for its systems engineering perspective, emphasizing embedded ML and control applications rather than pure data science.
Hakia Insight: Tennessee Tech's partnership with Nissan and Denso positions embedded ML specialists for a region where automotive manufacturing dominance creates unusual job security; unlike data science programs flooding the market, embedded ML engineers with control systems expertise command premium salaries in industrial settings.
At the master's level, tennessee Tech's machine learning program emphasizes practical engineering applications and real-world problem solving within a strong electrical and computer engineering context. The curriculum centers on applied machine learning for control systems, signal processing, and industrial automation—areas where the region's manufacturing and engineering sectors are actively recruiting. Students work on hands-on capstone projects deploying ML models in predictive maintenance, embedded systems, and autonomous vehicles. The program integrates circuit design, signal processing fundamentals, and modern deep learning techniques, giving graduates a rare combination of hardware understanding and ML expertise. Faculty research often bridges the gap between traditional controls engineering and contemporary neural network approaches, creating a distinctive angle for students interested in robotics, IoT, and smart systems. The institution's strong industry ties in Tennessee manufacturing and automotive sectors create direct pathways to employment. Career outcomes reflect this specialization: graduates excel in roles requiring both ML competency and systems-level thinking, particularly in companies building intelligent physical systems rather than pure software platforms.
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
- Electrical and Computer Engineering Research Center
Industry Partners
- Nissan North America (corporate)
- Denso (corporate)
Career Outcomes
Top Employers: Nissan, Denso, General Motors, Booz Allen Hamilton.
Accreditations and Certifications
Location Advantages: Proximity to automotive manufacturing hub (Nissan plant)Strong regional manufacturing and industrial baseCentral Tennessee location with access to Nashville tech ecosystem
The University of Tennessee-Chattanooga — Chattanooga, TN
Key Distinction: UTC combines rigorous machine learning fundamentals with embedded industry partnerships and applied projects in manufacturing and industrial AI, creating a practical pipeline to careers in data science and AI engineering.
Hakia Insight: UTC's integration of Tennessee Valley Authority innovation initiatives gives students rare access to real-time problems in grid modernization and energy systems—domains where ML is reshaping infrastructure but few universities offer project pipelines into actual deployment.
UTC's machine learning program emphasizes practical application through project-based learning and industry collaboration, positioning students to transition directly into data science and AI roles. The curriculum balances theoretical foundations in algorithms, statistics, and neural networks with hands-on experience in Python, TensorFlow, and cloud platforms. What sets this program apart is its integration with Chattanooga's growing tech ecosystem—students gain real-world exposure through capstone projects with local companies and partner organizations. The program particularly shines in applied machine learning for manufacturing and industrial systems, reflecting the region's economic focus. Faculty bring research experience in computer vision, natural language processing, and predictive analytics, ensuring coursework stays current with industry trends. Graduates frequently move into machine learning engineer, data scientist, and AI specialist roles at companies ranging from Fortune 500 firms to innovative startups. The smaller cohort size means stronger mentorship and more opportunities for individual research projects. UTC's location in Chattanooga—increasingly recognized as a tech talent hub—provides networking advantages and internship pipelines that many students leverage into full-time positions before graduation. Whether pursuing a bachelor's or master's degree, students benefit from faculty who actively consult with industry, bringing real problems and emerging techniques directly into the classroom.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Location Advantages: Chattanooga's emerging tech hub statusRegional manufacturing and industrial AI demandAccess to Tennessee Valley Authority (TVA) innovation initiatives
Tennessee State University — Nashville, TN
Key Distinction: TSU embeds machine learning education within a historically Black university context that emphasizes responsible AI development and equity considerations alongside technical depth.
Hakia Insight: Tennessee State's emphasis on responsible AI and equity considerations within a historically Black university context means graduates develop both technical depth and the institutional credibility to lead AI ethics initiatives—a competitive advantage as enterprises scramble to staff responsible AI teams.
At the master's level, as a historically Black university with significant research infrastructure, Tennessee State University's machine learning offerings reflect institutional strengths in applied computing and data science with particular attention to equitable access and representation in technical fields. The program leverages TSU's research centers and collaborative partnerships to engage students in substantive machine learning projects that contribute to published work and real-world problem-solving. Students gain experience with industrial-scale tools and methodologies through partnerships with technology companies and research initiatives, providing exposure to how machine learning operates in production systems rather than solely in academic settings. Faculty expertise spans multiple specializations—from computer vision and natural language processing to reinforcement learning and time-series analysis—allowing students to pursue depth in areas aligned with their career interests. The curriculum emphasizes mathematical foundations alongside practical implementation, ensuring graduates understand both the theoretical underpinnings and the engineering practices that successful practitioners need. Distinctive to TSU is its commitment to broadening participation in AI and machine learning fields; the program actively supports students from underrepresented backgrounds and creates mentoring networks that extend into industry. Students participate in research groups, attend technical conferences, and engage with internship opportunities at major technology firms and research institutions. The combination of rigorous technical training, research participation, and institutional commitment to diversity prepares graduates for leadership roles in machine learning and data science while contributing to a field that historically has lacked representation from Black technologists and researchers.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Location Advantages: Access to Nashville's tech corridor and healthcare sector companies
Southern Adventist University — Collegedale, TN
Key Distinction: Southern Adventist's program uniquely embeds ethical AI considerations and societal impact analysis throughout its machine learning curriculum.
Hakia Insight: Southern Adventist's embedded ethical AI curriculum isn't an afterthought seminar but woven through core coursework, producing graduates uniquely prepared for roles at organizations where AI governance has become a C-suite priority.
At the master's level, southern Adventist University's machine learning program emerges from strong computer science and mathematics foundations, offering students both theoretical rigor and practical application within a learning community that emphasizes ethical and responsible technology development. The curriculum progresses systematically through statistical concepts, algorithmic approaches, and implementation techniques, building toward advanced topics like deep learning and specialized applications in computer vision or natural language processing. Students engage in hands-on projects that span the full development lifecycle—from data acquisition and exploration through model training, evaluation, and deployment—using industry-standard tools and practices. The program's distinctive feature is its integration of computational ethics and responsible AI principles throughout the curriculum rather than as isolated electives; students regularly consider questions about fairness, transparency, and societal impact alongside technical optimization. Faculty combine academic research interests with mentoring that prepares students for diverse career paths, from data science roles in industry to further graduate study. Laboratory facilities and course projects provide access to substantial datasets and computational resources, enabling students to work with realistic problems rather than toy datasets. Partnerships with organizations in healthcare, finance, and technology sectors create internship opportunities and consulting projects where students apply machine learning to problems that matter beyond the classroom. Southern Adventist's intentional community ethos shapes a collaborative learning environment where students support each other's development and where diversity of background and perspective enriches classroom discussions about machine learning's role in society. Graduates report that this combination of technical depth, ethical grounding, and collaborative culture prepares them effectively for careers in data science, machine learning engineering, and related technical roles.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Location Advantages: Access to Chattanooga's growing tech ecosystem and nonprofit sector
University of Memphis — Memphis, TN
Key Distinction: Memphis distinguishes itself through active research partnerships with Fortune 500 logistics and healthcare companies, combined with faculty expertise in scalable ML systems and applied AI deployment.
Hakia Insight: Memphis's partnerships with FedEx and the FedEx Institute of Technology create a live laboratory for ML deployment in logistics at scale—students work with real supply chain data and optimization problems that textbooks can only approximate.
At the master's level, the University of Memphis machine learning program leverages the institution's research strengths in data science and computational methods, with a curriculum that balances mathematical foundations with contemporary AI applications. The program emphasizes statistical learning theory, optimization algorithms, and scalable machine learning systems, preparing students for roles in both research and industry settings. Memphis has developed partnerships with regional healthcare systems and logistics companies—particularly FedEx, headquartered in the city—creating internship and research opportunities in real-world ML deployment. The graduate program attracts students seeking rigorous training in deep learning, reinforcement learning, and machine vision, often paired with domain expertise in healthcare informatics or supply chain optimization. Faculty research groups actively pursue NSF-funded projects in machine learning applications, giving graduate students access to funded research positions. Memphis's location in a major logistics and healthcare hub provides direct access to companies deploying machine learning at scale, and many graduates transition into senior data science and research engineer roles at these organizations or tech firms nationwide.
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
- Computational Intelligence Laboratory
- NIH mDOT Center
- MD2K Center of Excellence
- Center for Information Assurance
- Center for Disaster Recovery and Resiliency
- Electroptics and Remote Sensors Laboratory
- Autonomous & Complex Systems Laboratory
Industry Partners
- FedEx (corporate)
- FedEx Institute of Technology (sponsor)
- Defense Human Resources Activity (sponsor)
- Department of Defense (sponsor)
- US Department of Transportation (sponsor)
- US Department of Labor (sponsor)
- City of Memphis (collaborator)
Career Outcomes
Top Employers: FedEx, Healthcare systems in the Mid-South.
Notable Faculty
- Dr. Deepak Venugopal — Machine learning and artificial intelligence
- Dr. Santosh Kumar — Artificial intelligence for wearables and mobile sensor big data
- Dr. Dipankar Dasgupta — Bio-inspired computing, cybersecurity, trustworthy AI
- Dr. Bonny Banerjee — Computational Intelligence, machine learning, cognitive science
- Dr. Xiaolei Huang — Natural language processing and machine learning
- Dr. Haomiao Ni — Computer vision, machine learning, artificial intelligence
- Dr. Kan Yang — Adversarial machine learning and data security
Location Advantages: FedEx headquarters presenceMajor healthcare and medical research institutionsCentral logistics and supply chain industry hub
Best Doctoral Machine Learning Degree Programs in Tennessee
Vanderbilt University — Nashville, TN
Key Distinction: Vanderbilt's machine learning program stands out for its integrated healthcare AI research pipeline and medical center partnerships, rare among peer institutions.
Hakia Insight: Vanderbilt's integrated healthcare AI pipeline through partnerships with HCA Healthcare and its medical center gives doctoral students rare access to clinical datasets and problems; most top-tier ML PhDs produce papers, but Vanderbilt graduates often produce deployed systems affecting patient care.
At the doctoral level, vanderbilt's machine learning offerings emerge from a strong electrical engineering and computer science foundation, with particular depth in deep learning, computer vision, and natural language processing. The program benefits from the institution's research intensity and Nashville's growing tech ecosystem. Faculty-led research groups tackle applications spanning healthcare AI, autonomous systems, and speech processing, creating pipelines for students to move directly into research roles. The computer science curriculum emphasizes both theoretical rigor and practical implementation, with courses in neural networks, probabilistic graphical models, and reinforcement learning. Graduate students frequently collaborate with faculty on published research, and the proximity to Vanderbilt Medical Center opens unique opportunities in healthcare AI and biomedical signal processing. Career outcomes are strong, with graduates placed at major tech firms, startups, and research institutions. The program's strength lies in balancing academic depth with applied research exposure—students aren't just learning ML theory in isolation but engaging with real problems in healthcare, robotics, and data science from day one.
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
- Vanderbilt Institute for Software Integrated Systems (ISIS)
- Learning and Reasoning Lab
Industry Partners
- HCA Healthcare (corporate)
- Amazon (corporate)
- Google (corporate)
Career Outcomes
Top Employers: Google, Amazon, Microsoft, Meta.
Notable Faculty
- Yaoyu Cheng — Machine learning in medical imaging and healthcare AI
- Gabor Karsai — Embedded systems and cyber-physical systems with machine learning
Accreditations and Certifications
- ABET accredited (engineering programs)
Location Advantages: Nashville tech ecosystem growthProximity to Vanderbilt Medical Center for healthcare AI applicationsRegional hub for healthcare and financial services companies
Middle Tennessee State University — Murfreesboro, TN
Key Distinction: MTSU's machine learning program prioritizes accessibility and interdisciplinary application, building competent practitioners from diverse backgrounds and equipping them for roles across industries beyond tech.
Hakia Insight: MTSU's deliberate focus on accessibility and interdisciplinary backgrounds means its doctoral pipeline feeds talent into healthcare, finance, and energy sectors beyond Big Tech—a strategic positioning as companies beyond Silicon Valley build in-house ML capacity.
At the doctoral level, MTSU's approach to machine learning education centers on accessibility and breadth—the program welcomes students from diverse technical backgrounds and builds them into competent practitioners through incremental skill development. Rather than assuming advanced mathematics prerequisites, the curriculum scaffolds students from fundamentals through advanced topics, covering data preprocessing, feature engineering, supervised and unsupervised learning, and deep learning architectures. The program stands out for its flexibility: students can pursue machine learning as a concentration within computer science, data science, or engineering programs, allowing customization based on career goals. MTSU emphasizes interdisciplinary applications, encouraging students to apply machine learning to problems in education, healthcare, business analytics, and social sciences—not just pure computer science domains. Lab work is woven throughout, with access to modern computing resources and cloud platforms for training and deploying models. Faculty expertise spans machine learning systems, optimization, and applications in real-world domains. The university's location in Murfreesboro, near Nashville's growing tech corridor, offers internship and networking opportunities with companies increasingly relocating to Middle Tennessee. MTSU graduates enter roles ranging from junior data analysts to machine learning engineers, many reporting strong salary growth within 2–3 years of graduation. The program also supports students pursuing further education, with strong preparation for PhD programs in machine learning and related fields.
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
- QRISE Center
- Undergraduate Research Center
Industry Partners
- St. Jude's Children's Hospital (employer)
- Oak Ridge National Laboratory (employer)
- Vanderbilt Wond'ry (sponsor)
- NSF I-Corps (sponsor)
Notable Faculty
- Dr. John Wallin — Computational and Data Science Program Director
- Dr. Misa Faezipour — Health systems engineering using machine learning and optimization
- Dr. Lei Miao — Reinforcement learning for intelligent transportation systems and wireless networks
- Dr. Jorge Vargas — Autonomous vehicle sensor systems and hardware-in-the-loop testing
Location Advantages: Proximity to Nashville's tech and fintech growthAccess to Tennessee innovation and entrepreneurship networks
The University of Tennessee-Knoxville — Knoxville, TN
Key Distinction: Full funding for all students ($36,000 annual stipend + tuition waiver + health insurance). Faculty-to-student ratio 1:1
Hakia Insight: UT-Knoxville's 1:1 faculty-to-student ratio with full funding ($36K stipend plus tuition) and a cohort capped at two admits annually creates genuine research partnership rather than advisor juggling—the model mimics top-tier programs but at a school where your advisor isn't managing 15 students.
The Finance Ph.D. program is a STEM-designated 4-5 year program that admits only 2 students annually, maintaining a 1:1 research faculty to student ratio. Students receive full funding with $36,000 annual stipend, complete tuition waiver, and health insurance benefits. The program requires 48 credit hours excluding dissertation, with comprehensive examinations following the second year. Students complete 5 finance seminars plus economics and research methods courses. After passing comprehensive exams around summer of year 2, students focus on dissertation research. The program emphasizes academic placement with recent graduates securing tenure-track positions at universities like Western Kentucky University, Loyola Maryland, and East Carolina University, though some enter industry roles at Citi Bank and government positions at SEC. Students are mentored as junior colleagues from day one, with opportunities for coauthored publications and professional development through conferences and research seminars.
Programs Offered
- Ph.D. in Finance — 4-6 years, on-campus. Ph.D.
Research Labs and Institutes
- Institute for Advanced Computational Science
- Innovative Computing Laboratory (ICL)
Industry Partners
- Oak Ridge National Laboratory (government)
- NVIDIA (corporate)
- IBM (corporate)
Notable Faculty
- Stanimire Tomov — GPU-accelerated machine learning, linear algebra software
- Jiajia Li — Distributed machine learning, high-performance computing
Admissions
GPA Requirement: 3.0 (3.3 for international students). Application Deadline: January 15 (priority deadline).
Requirements: 5 finance seminars, Economics courses, Research methods courses, Second-year research paper, Comprehensive examinations, Dissertation
Accreditations and Certifications
Location Advantages: Oak Ridge National Laboratory partnership and proximityAccess to supercomputing infrastructure (Summit, Frontier)Regional hub for scientific computing and energy research
University of Memphis — Memphis, TN
Key Distinction: Customized course planning to fit individual student needs and prior training. Faculty publish in premier journals (MIS Quarterly, Information Systems Research, Management Science)
Hakia Insight: Memphis's MIS PhD with customizable coursework and faculty publishing in tier-one journals (MIS Quarterly, Information Systems Research) attracts students building academic or executive careers; the program's corporate pipeline through FedEx and defense agencies makes it rare for a PhD track.
The PhD in Management Information Systems (MIS) at the University of Memphis is a 72-credit hour program designed for academic careers and managerial positions in corporations. Students complete 12 hours of research core (including econometrics and multivariate methods), 30 hours of MIS concentration coursework (covering business analytics, database systems, business machine learning, and information security), 15 hours of dissertation work, and 15 hours of additional graduate coursework. The program offers customized course planning to fit individual student needs and prior training. Faculty publish in premier journals including MIS Quarterly, Information Systems Research, and Management Science, with several serving on editorial boards. Recent graduates have secured assistant professor positions at Virginia Tech and Clemson University. PhD students work closely with faculty on research and have published in top-tier journals like MISQ and Journal of Operations Management based on their dissertation work. Faculty have received external grants from corporations like FedEx and agencies including NIH and Department of Homeland Security.
Programs Offered
- PhD - Management Information Systems — 4-6 years, on-campus. PhD
Research Labs and Institutes
- Computational Intelligence Laboratory
- NIH mDOT Center
- MD2K Center of Excellence
- Center for Information Assurance
- Center for Disaster Recovery and Resiliency
- Electroptics and Remote Sensors Laboratory
- Autonomous & Complex Systems Laboratory
Industry Partners
- FedEx (corporate)
- FedEx Institute of Technology (sponsor)
- Defense Human Resources Activity (sponsor)
- Department of Defense (sponsor)
- US Department of Transportation (sponsor)
- US Department of Labor (sponsor)
- City of Memphis (collaborator)
Notable Faculty
- Dr. Deepak Venugopal — Machine learning and artificial intelligence
- Dr. Santosh Kumar — Artificial intelligence for wearables and mobile sensor big data
- Dr. Dipankar Dasgupta — Bio-inspired computing, cybersecurity, trustworthy AI
- Dr. Bonny Banerjee — Computational Intelligence, machine learning, cognitive science
- Dr. Xiaolei Huang — Natural language processing and machine learning
- Dr. Haomiao Ni — Computer vision, machine learning, artificial intelligence
- Dr. Kan Yang — Adversarial machine learning and data security
Location Advantages: FedEx headquarters presenceMajor healthcare and medical research institutionsCentral logistics and supply chain industry hub
