Best Bachelor's Machine Learning Degree Programs in Maryland
University of Maryland-College Park — College Park, MD
Key Distinction: Capstone in Machine Learning (CMSC473) project course. Specialization requires breadth across five distributional areas
Hakia Insight: UMD College Park's location 30 minutes from NIST and federal agencies gives students direct access to government ML research—rare for undergrads—while faculty like Furong Huang (optimization theory) and Dinesh Manocha (computer vision) anchor the program in cutting-edge research that shapes both academia and policy.
The Bachelor of Science in Computer Science with a Machine Learning specialization at University of Maryland-College Park provides a rigorous foundation in computational methods, artificial intelligence, and data science. Students complete core lower-level courses in mathematics and computer science fundamentals, followed by specialized upper-level coursework in machine learning, deep learning, computer vision, and natural language processing. The program culminates in CMSC 473 (Capstone in Machine Learning), a hands-on project course. The curriculum requires students to fulfill upper-level computer science requirements across at least three of five distributional areas (Systems, Information Processing, Software Engineering and Programming Languages, Theory, and Numerical Analysis), ensuring broad technical competency. The specialization emphasizes practical applications through courses like Introduction to Data Science, Introduction to Artificial Intelligence, and Computational Methods, preparing graduates for roles in machine learning engineering, data science, and AI development.
Programs Offered
- Bachelor of Science in Computer Science with Machine Learning Specialization — 4 years, on-campus. BS
Research Labs and Institutes
- University of Maryland Institute for Advanced Computer Studies (UMIACS)
- Perception and Robotics Group
- Natural Language Processing Group
Industry Partners
- Microsoft (corporate)
- Google (corporate)
- Amazon (corporate)
- NIST (government)
- NSA (government)
- Naval Research Laboratory (NRL) (government)
Career Outcomes
Median Salary: $NaN.
Notable Faculty
- Furong Huang — Machine learning theory, optimization, neural network training
- Dinesh Manocha — Computer vision, robotics, autonomous systems
- Jordan Boyd-Graber — Natural language processing, machine learning
Accreditations and Certifications
Location Advantages: Proximity to National Institute of Standards and Technology (NIST) for government partnerships30 minutes from Washington, D.C. federal agencies and policy centers45 minutes from Baltimore biomedical and healthcare tech corridorIntegrated partnerships with NSA and Naval Research Laboratory
University of Maryland-Baltimore County — Baltimore, MD
Key Distinction: ABET-accredited program. Optional specialization tracks including AI/ML, Data Science, Cybersecurity, and Game Development
Hakia Insight: UMBC's partnership with Johns Hopkins APL and proximity to NSA creates a specialized pipeline into defense-sector ML roles that most undergraduate programs simply don't offer; students work on real anomaly detection and cybersecurity ML problems rather than textbook examples.
The Bachelor of Science in Computer Science at UMBC is an ABET-accredited program preparing students for careers in the computing industry and graduate studies. The curriculum requires 120 credits across programming, discrete structures, data structures, operating systems, algorithms, software engineering, and mathematics. Students must complete a minimum of 75 credits in major requirements with a minimum grade of C (B for gateway courses). The program offers optional specialization tracks in Artificial Intelligence and Machine Learning, Data Science, Cybersecurity, and Game Development, each adding 12-19 credits of focused coursework. The AI/ML track includes core courses in Introduction to Artificial Intelligence and Introduction to Machine Learning, with electives in Computer Vision, Natural Language Processing, Neural Networks, and Robotics. Computing jobs are among the fastest growing and highest paid in the country according to the U.S. Bureau of Labor Statistics. UMBC computer science graduates are employed by tech industry leaders, government agencies, the defense industry, and video game companies, with many admitted to top graduate programs.
Programs Offered
- Bachelor of Science in Computer Science — 4 years, on-campus. BS
Research Labs and Institutes
- Center for Accelerated Real-Time Analytics (CARTA)
- Cyber Defense Lab
Industry Partners
- Northrop Grumman (corporate)
- Lockheed Martin (corporate)
- Johns Hopkins University Applied Physics Laboratory (government)
Notable Faculty
- Haimonti Dutta — Machine learning for cybersecurity and anomaly detection
- Konstantinos Michmizos — Computational neuroscience and machine learning
Accreditations and Certifications
Location Advantages: Proximity to Baltimore-Washington tech corridorAccess to defense and intelligence sector employers (NSA, APL, Northrop Grumman)Close ties to Johns Hopkins research ecosystem
Towson University — Towson, MD
Key Distinction: Towson's machine learning program excels at serving working professionals and part-time learners while maintaining strong regional employer connections and practical, hands-on learning emphasis.
Hakia Insight: Towson deliberately targets working professionals and part-time learners in a field where most competitors assume full-time enrollment, meaning you can earn a specialized ML degree without pausing your career.
At the bachelor's level, towson's computer science program integrates machine learning as a key specialization within a curriculum emphasizing practical software engineering and real-world application. Students engage with machine learning fundamentals through courses in algorithms, data structures, and statistics, then advance into specialized electives covering supervised learning, unsupervised learning, and deep learning. The program's strength lies in its accessibility to working professionals and part-time learners—many students are employed in the Baltimore-Washington region while completing their degree. Towson faculty bring industry experience alongside academic expertise, creating a program culture that bridges classroom concepts with immediate career relevance. Internship placements are facilitated through relationships with regional tech companies, healthcare systems, and consulting firms, allowing students to apply machine learning techniques to real datasets early in their studies. The university's proximity to major employers in Maryland and proximity to Johns Hopkins and other research institutions creates networking opportunities often unavailable at programs further from urban tech hubs. While Towson's research labs are more modest compared to large research universities, the focus on student-centered learning and mentorship creates strong peer communities. For students balancing education with work or those seeking a more accessible, application-focused path to machine learning expertise, Towson offers competitive preparation with strong regional job market alignment.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Industry Partners
- Salisbury University (nonprofit)
- Regional Maryland tech companies (corporate)
Accreditations and Certifications
Location Advantages: Proximity to Baltimore-Washington metro area employersAccess to regional tech companies and corporate internship opportunitiesLocated near Johns Hopkins and other research institutions
United States Naval Academy — Annapolis, MD
Hakia Insight: The Naval Academy's full-scholarship model eliminates the financial calculus entirely, allowing you to focus on one-on-one faculty research and direct contribution to national security challenges—a combination unavailable at any civilian institution.
At the bachelor's level, USNA's Computer Science program offers a nationally recognized curriculum with full scholarship funding, one-on-one faculty research opportunities, and direct contributions to Naval operations through capstone projects that have saved over $10 million in contracting fees. The program features specialized tracks, cutting-edge research integration, and guaranteed post-graduation employment as Naval officers.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages:
Loyola University Maryland — Baltimore, MD
Key Distinction: Distinctive for embedding ethical AI and responsible data science principles throughout the curriculum rather than as an afterthought, appealing to students who want ML skills grounded in humanistic inquiry.
Hakia Insight: Loyola embeds ethical AI from day one rather than tacking it on as a capstone afterthought, producing graduates equipped to answer 'should we deploy this model?' as rigorously as 'can we build it?'—increasingly critical as companies face regulatory and reputational pressure.
At the bachelor's level, loyola's machine learning curriculum emphasizes ethical AI and responsible data science from the ground up, a philosophy that permeates both coursework and capstone projects. The program weaves together core ML fundamentals with a strong liberal arts ethos, requiring students to grapple with the societal implications of algorithmic decision-making—particularly relevant for those considering roles in finance, healthcare, or government sectors where bias and transparency matter. You'll encounter hands-on projects in natural language processing, computer vision, and predictive analytics, with faculty who actively publish in peer-reviewed venues. The Jesuit institution's proximity to Baltimore's growing tech corridor and partnerships with regional employers in financial services and healthcare create internship pipelines that often convert to full-time offers. Graduates report strong placement in roles spanning data science, machine learning engineer, and analytics positions, with many citing the program's emphasis on communication skills (a Loyola hallmark) as a competitive edge when interviewing at top firms.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Industry Partners
- Mercy Medical Center (corporate)
- BGE (Baltimore Gas and Electric) (corporate)
Location Advantages: Proximity to Baltimore tech corridorAccess to healthcare and financial services employers in Mid-Atlantic region
Hood College — Frederick, MD
Key Distinction: Distinguished by making machine learning accessible and rigorous without sacrificing understanding, with particular strength in applications to biology, environmental, and social science domains.
Hakia Insight: Hood College deliberately orients its ML curriculum toward biology, environmental science, and social science applications rather than finance or tech, creating rare opportunities for students who want technical depth but reject the Silicon Valley monoculture.
At the bachelor's level, hood College's approach to machine learning balances technical rigor with accessible pedagogy, making it particularly welcoming for students transitioning into ML from non-traditional backgrounds or returning to education mid-career. The program emphasizes foundational mathematics and algorithms before advancing to applied projects, ensuring students truly understand the "why" behind techniques rather than simply stacking libraries. You'll work with real datasets in courses covering supervised and unsupervised learning, deep neural networks, and reinforcement learning, with particular strength in applications to biology, environmental science, and social science research—areas where Hood's liberal arts mission naturally connects. The collaborative culture means close relationships with faculty mentors who genuinely know your goals and can guide independent study projects aligned with your interests. Nestled in Maryland's Frederick region between Baltimore and Washington D.C., Hood graduates find internships and early-career positions at both regional tech companies and larger employers in the D.C. metro area who value the program's emphasis on clear thinking and communication.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages: Located between Baltimore and Washington D.C. tech marketsProximity to federal and regional employers
Coppin State University — Baltimore, MD
Key Distinction: Distinctive for intentionally building ML talent pipelines within underrepresented communities, combining rigorous technical training with robust mentorship and career support.
Hakia Insight: Coppin State's intentional focus on building ML talent pipelines within underrepresented communities includes explicit mentorship structures designed to persist past graduation—a model that statistically improves retention in tech careers where many underreps otherwise plateau.
At the bachelor's level, coppin's computer science program, including its machine learning curriculum, is deliberately designed to build a diverse pipeline into technical fields, with explicit mentorship and bridge support for first-generation students and those from underrepresented backgrounds in tech. The ML track within the CS degree emphasizes foundational computer science and mathematics, ensuring students develop genuine fluency rather than relying on shortcut frameworks. Coursework covers core algorithms, statistical learning, supervised and unsupervised methods, and applications in areas like image processing and pattern recognition. As a historically Black university in Baltimore, Coppin has deep community connections and partnerships with local employers and nonprofits seeking talented ML practitioners from diverse backgrounds. The program's strength lies in its supportive academic environment—smaller cohorts, accessible faculty, and peer collaboration—combined with intentional pathways to internships and employment. Graduates have moved into roles at tech companies, government agencies, and Baltimore-based organizations, with many citing the program's holistic approach to professional development alongside technical skill-building.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Industry Partners
- Baltimore City Government (government)
- Urban Tech nonprofits (nonprofit)
Location Advantages: Located in Baltimore with community and government connectionsPartnerships with local nonprofits and city agencies
Washington Adventist University — Takoma Park, MD
Key Distinction: Washington Adventist University offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: Washington Adventist University provides accessible ML education in Takoma Park with direct proximity to DC federal agencies and tech corridors.
Washington Adventist University offers Machine Learning programs in Takoma Park, MD. As a private institution, it provides accessible education pathways for students in the region.
Washington College — Chestertown, MD
Key Distinction: Washington College offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: Washington College offers ML programs in Chestertown with accessible pathways for regional students entering the technology sector.
Washington College offers Machine Learning programs in Chestertown, MD. As a private institution, it provides accessible education pathways for students in the region.
Frostburg State University — Frostburg, MD
Key Distinction: A regionally-focused program where ML training is deliberately embedded in cross-disciplinary capstone projects, emphasizing applied problem-solving over algorithm breadth.
Hakia Insight: Frostburg anchors ML training in cross-disciplinary capstones tied to Appalachian manufacturing and environmental data rather than generic algorithmic exercises, producing graduates who can justify ML investments to non-tech industries that are often overlooked by major programs.
At the bachelor's level, frostburg's approach to machine learning prioritizes cross-disciplinary collaboration, allowing students to anchor their ML training in domain-specific applications rather than treating algorithms as abstract tools. Computer science faculty work closely with colleagues in biology, chemistry, environmental science, and business to design projects where students deploy classification, clustering, and predictive models on real institutional and regional datasets. This structure appeals to students who want context for their learning—whether analyzing environmental sensor networks in Appalachia or optimizing supply chains for small manufacturers in the region. The core curriculum covers supervised and unsupervised learning, neural networks, and deep learning, but the distinguishing feature is the capstone requirement: students must complete a substantial ML project solving a problem outside the computer science department. This forces breadth and forces relevance. Frostburg's smaller cohorts mean closer faculty relationships and more personalized feedback on projects. The university's location in western Maryland, while rural, provides access to undergraduate research funding and partnerships with regional industries facing real optimization challenges. Graduates often move into roles at mid-market companies, healthcare systems, and manufacturing firms rather than concentrating at big tech—a shift many students find refreshing, offering better work-life balance and clearer impact on day-to-day operations.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages: Regional partnerships with mid-market manufacturing and healthcare organizationsAccess to environmental and agricultural data from Appalachian region
Best Master's Machine Learning Degree Programs in Maryland
University of Maryland-Baltimore County — Baltimore, MD
Key Distinction: Thesis vs. non-thesis track options. Machine learning specialization with courses in knowledge-intensive learning, preference learning, unsupervised perceptual learning, and privacy-preserving data mining
Hakia Insight: UMBC's thesis-vs-non-thesis flexibility for working professionals combines with specialization depth (privacy-preserving data mining, unsupervised learning) and proximity to defense contractors, making it a rare path for professionals who want research rigor without leaving their jobs.
UMBC's M.S. in Computer Science offers both thesis and non-thesis tracks to accommodate working professionals. The thesis option requires 30 credits including 6 credits of thesis research (CMSC 799) with oral defense, while the non-thesis option requires 33 credits of coursework. Both tracks require completion of core courses including CMSC 641 Algorithms, plus electives in specialized areas such as machine learning, cybersecurity, databases, and natural language processing. The program must be completed within five years with a minimum 3.0 GPA. While specific salary data and assistantship details are not provided on this page, the program emphasizes research depth through thesis completion or breadth through coursework-only options, allowing mid-career professionals to advance technical expertise in high-demand AI/ML specializations.
Programs Offered
- Master of Science in Computer Science — 1-2 years, on-campus. MS
Research Labs and Institutes
- Center for Accelerated Real-Time Analytics (CARTA)
- Cyber Defense Lab
Industry Partners
- Northrop Grumman (corporate)
- Lockheed Martin (corporate)
- Johns Hopkins University Applied Physics Laboratory (government)
Notable Faculty
- Haimonti Dutta — Machine learning for cybersecurity and anomaly detection
- Konstantinos Michmizos — Computational neuroscience and machine learning
Accreditations and Certifications
Location Advantages: Proximity to Baltimore-Washington tech corridorAccess to defense and intelligence sector employers (NSA, APL, Northrop Grumman)Close ties to Johns Hopkins research ecosystem
University of Maryland-College Park — College Park, MD
Key Distinction: Non-thesis track only. 30 credits total (reduced credit requirement for working professionals)
Hakia Insight: The M.P.S. at UMD College Park compresses a rigorous ML master's into 30 credits with no thesis requirement, then positions graduates 30 minutes from NIST and federal agencies—a formula that trades depth for speed and placement into government roles few other programs service.
The Master of Professional Studies (M.P.S.) in Machine Learning at University of Maryland is a 30-credit, non-thesis program designed for working professionals. The curriculum emphasizes core competencies in probability, statistics, data science, machine learning principles, optimization, and computing systems. Students complete 18 credits of required foundational courses and 12 credits of electives, allowing flexibility to tailor their specialization. The program does not offer a thesis track, focusing instead on coursework-based learning for efficient completion. While specific part-time scheduling, assistantship opportunities, embedded certifications, and employer partnerships are not detailed in this catalog entry, the streamlined credit requirement and professional focus suggest suitability for mid-career advancement. Graduates typically advance into senior data science and machine learning engineering roles with increased earning potential.
Programs Offered
- Machine Learning, Master of Professional Studies — 1-2 years, on-campus. M.P.S.
Research Labs and Institutes
- University of Maryland Institute for Advanced Computer Studies (UMIACS)
- Perception and Robotics Group
- Natural Language Processing Group
Industry Partners
- Microsoft (corporate)
- Google (corporate)
- Amazon (corporate)
- NIST (government)
- NSA (government)
- Naval Research Laboratory (NRL) (government)
Career Outcomes
Median Salary: $NaN.
Notable Faculty
- Furong Huang — Machine learning theory, optimization, neural network training
- Dinesh Manocha — Computer vision, robotics, autonomous systems
- Jordan Boyd-Graber — Natural language processing, machine learning
Accreditations and Certifications
Location Advantages: Proximity to National Institute of Standards and Technology (NIST) for government partnerships30 minutes from Washington, D.C. federal agencies and policy centers45 minutes from Baltimore biomedical and healthcare tech corridorIntegrated partnerships with NSA and Naval Research Laboratory
Towson University — Towson, MD
Key Distinction: Thesis-required capstone (no coursework-only track mentioned). Accelerated bachelor's-master's (4+1) pathway available for Towson undergraduates: up to 9 graduate units apply to both degrees, enabling completion in as little as 12 months with tuition savings
Hakia Insight: Towson's 4+1 accelerated bachelor-to-master pathway lets undergraduates complete both degrees in 12 months with tuition savings and immediate entry into an Economic Analytics program—a structural advantage that eliminates the traditional gap year most ML professionals face.
The Economic Analytics M.S. is a 33-unit thesis-required program designed for working professionals seeking advanced skills in data science and econometrics. Students combine economic theory with machine learning and computational methods to assess causal policy impacts. The program can be completed in 16 months (or as little as 12 months through the accelerated 4+1 pathway for Towson undergraduates). Courses span foundations in economic theory, methods in econometrics and machine learning (using R, Stata, and Python), and applied impact evaluation. The thesis capstone requires independent research applying learned techniques. Graduates are positioned for mid-career advancement into data analyst, economist, or statistician roles in finance, banking, healthcare, government, consulting, and NGOs. The program also serves as preparation for Ph.D. study in economics or related fields. No information provided on part-time/evening scheduling, assistantships, embedded certifications, or salary outcomes.
Programs Offered
- Economic Analytics M.S. — 1-2 years, on-campus. MS
Industry Partners
- Salisbury University (nonprofit)
- Regional Maryland tech companies (corporate)
Accreditations and Certifications
Location Advantages: Proximity to Baltimore-Washington metro area employersAccess to regional tech companies and corporate internship opportunitiesLocated near Johns Hopkins and other research institutions
Johns Hopkins University — Baltimore, MD
Key Distinction: Two program tracks: course-only (36 credits, no thesis) or research track with year-long faculty-mentored capstone project. No GRE required; no application fee
Hakia Insight: Johns Hopkins eliminates the GRE and application fee while offering a unique dual-track model (coursework-only or year-long capstone), then connects you to NIH biomedical datasets and JHU Hospital clinicians—positioning data science graduates for leadership in healthcare AI, where domain context is often the real bottleneck.
Johns Hopkins' Master of Science in Engineering (MSE) in Data Science prepares working professionals for leadership in data science and AI. The program offers two tracks: a course-only option (36 credits, ~3-4 semesters full-time) and a research track with a year-long capstone project with faculty mentors. No GRE required. Select exceptional students gain paid summer internship opportunities at Johns Hopkins Applied Physics Lab. The program emphasizes real-world applications across healthcare, finance, national security, and sustainable energy. Graduates work at Amazon, TikTok, Accenture, and Dana-Farber Cancer Institute. According to the Bureau of Labor Statistics, data scientists represent the fastest-growing professional sector with 42% job growth expected 2023–2033. Alumni benefit from Johns Hopkins' global network and deep industry connections. Tuition is $33,335 per semester.
Programs Offered
- Master of Science in Engineering in Data Science — 1-2 years, on-campus. MSE
Research Labs and Institutes
- Computer Vision Lab
- Computational Sensorimotor Systems Lab
- Statistical Machine Learning Group
Industry Partners
- JHU Applied Physics Laboratory (government)
- Lockheed Martin (corporate)
- Northrop Grumman (corporate)
- National Institutes of Health (NIH) (government)
Career Outcomes
Top Employers: Amazon.
Notable Faculty
- Rene Vidal — Computer vision, matrix completion, dynamical systems
- Alan Yuille — Computer vision, deep learning, computational models of vision
- Greg Hager — Surgical robotics, computer vision, human-robot interaction
Accreditations and Certifications
Location Advantages: Proximity to National Institutes of Health (NIH) for biomedical datasets and partnershipsAccess to Johns Hopkins Hospital and health system for clinical AI collaborationsBaltimore region hub for defense contractors and aerospace (Lockheed Martin, Northrop Grumman, APL)Proximity to Washington, D.C. government agencies and policy centers
Hood College — Frederick, MD
Key Distinction: Distinguished by making machine learning accessible and rigorous without sacrificing understanding, with particular strength in applications to biology, environmental, and social science domains.
Hakia Insight: Hood College's master's program brings the same accessible-yet-rigorous approach to graduate study, with particular strength in biology and environmental applications that larger programs marginalize.
At the master's level, hood College's approach to machine learning balances technical rigor with accessible pedagogy, making it particularly welcoming for students transitioning into ML from non-traditional backgrounds or returning to education mid-career. The program emphasizes foundational mathematics and algorithms before advancing to applied projects, ensuring students truly understand the "why" behind techniques rather than simply stacking libraries. You'll work with real datasets in courses covering supervised and unsupervised learning, deep neural networks, and reinforcement learning, with particular strength in applications to biology, environmental science, and social science research—areas where Hood's liberal arts mission naturally connects. The collaborative culture means close relationships with faculty mentors who genuinely know your goals and can guide independent study projects aligned with your interests. Nestled in Maryland's Frederick region between Baltimore and Washington D.C., Hood graduates find internships and early-career positions at both regional tech companies and larger employers in the D.C. metro area who value the program's emphasis on clear thinking and communication.
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: Located between Baltimore and Washington D.C. tech marketsProximity to federal and regional employers
Frostburg State University — Frostburg, MD
Key Distinction: A regionally-focused program where ML training is deliberately embedded in cross-disciplinary capstone projects, emphasizing applied problem-solving over algorithm breadth.
Hakia Insight: Frostburg's deliberately constrained geographic footprint—anchoring ML projects to Appalachian manufacturing and agricultural data—forces students to develop domain expertise that larger programs treat as optional, creating graduates who can architect solutions rather than just tune hyperparameters.
At the master's level, frostburg's approach to machine learning prioritizes cross-disciplinary collaboration, allowing students to anchor their ML training in domain-specific applications rather than treating algorithms as abstract tools. Computer science faculty work closely with colleagues in biology, chemistry, environmental science, and business to design projects where students deploy classification, clustering, and predictive models on real institutional and regional datasets. This structure appeals to students who want context for their learning—whether analyzing environmental sensor networks in Appalachia or optimizing supply chains for small manufacturers in the region. The core curriculum covers supervised and unsupervised learning, neural networks, and deep learning, but the distinguishing feature is the capstone requirement: students must complete a substantial ML project solving a problem outside the computer science department. This forces breadth and forces relevance. Frostburg's smaller cohorts mean closer faculty relationships and more personalized feedback on projects. The university's location in western Maryland, while rural, provides access to undergraduate research funding and partnerships with regional industries facing real optimization challenges. Graduates often move into roles at mid-market companies, healthcare systems, and manufacturing firms rather than concentrating at big tech—a shift many students find refreshing, offering better work-life balance and clearer impact on day-to-day operations.
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: Regional partnerships with mid-market manufacturing and healthcare organizationsAccess to environmental and agricultural data from Appalachian region
Morgan State University — Baltimore, MD
Key Distinction: Morgan State emphasizes machine learning applications in healthcare, social impact, and government, with mentorship-rich training and ethical AI foundations.
Hakia Insight: Morgan State's pipeline to Johns Hopkins APL and NSA isn't incidental; the mentorship structure explicitly builds ethical AI literacy alongside technical depth, meaning graduates enter federal roles already fluent in responsible ML governance rather than learning it on the job.
At the master's level, morgan State's machine learning initiatives align with the university's mission to serve underrepresented populations in STEM and build talent pipelines into tech careers. The program emphasizes foundational machine learning theory alongside applications in healthcare, environmental science, and social impact computing—areas where Morgan faculty have demonstrated research strength. Students benefit from relatively small cohort sizes and direct faculty mentorship, a contrast to larger research universities where graduate students can become anonymous. Morgan's location in Baltimore positions graduates near growing tech corridors and provides partnership opportunities with Johns Hopkins University, the National Security Agency, and regional technology companies. The curriculum integrates ethics and fairness in machine learning, reflecting institutional commitment to responsible AI development. Research opportunities often center on applied problems: predictive health analytics, climate data modeling, and computational social science. While Morgan's machine learning program is still developing its research infrastructure compared to R1 institutions, the university's investment in computing facilities and faculty recruitment in AI signifies institutional priority. Graduates frequently transition into roles at federal research centers, healthcare technology firms, and government agencies, where diversity and contextual problem-solving skills are increasingly valued. The supportive environment and emphasis on both rigor and equity create a distinctive path for students committed to machine learning careers with broader societal impact.
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
- Johns Hopkins University Applied Physics Laboratory (government)
- National Security Agency (government)
Career Outcomes
Top Employers: Johns Hopkins APL, National Security Agency, Booz Allen Hamilton.
Location Advantages: Baltimore proximity to Johns Hopkins, APL, and NSAConnections to federal research and intelligence agencies
Best Doctoral Machine Learning Degree Programs in Maryland
University of Maryland-College Park — College Park, MD
Key Distinction: A large research university with specialized MS/PhD tracks in ML, integrated with UMIACS and federal lab partnerships, offering strong placement outcomes and proximity to both government research and D.C./Baltimore tech hubs.
Hakia Insight: UMD-College Park's UMIACS integration gives doctoral students real-time access to government research agendas through NIST partnerships, effectively letting you shape your dissertation around problems the federal government will fund and hire you to solve.
At the doctoral level, the University of Maryland's machine learning program stands out for its integration of theory and practice within a large, research-intensive ecosystem where students encounter diverse application domains from day one. The Department of Computer Science offers both a specialized MS in Machine Learning and a PhD program with multiple research tracks—computer vision, natural language processing, reinforcement learning, and systems—each backed by active, well-funded faculty labs. Students benefit from proximity to the University of Maryland Institute for Advanced Computer Studies (UMIACS), a collaborative research center where computer scientists, engineers, and domain experts converge on large-scale problems. The curriculum is modern and competitive: students cover foundational ML theory, deep learning architectures, and recent advances in areas like transformer models and causal reasoning, often through instructors who are actively publishing in top conferences. A distinctive feature is the breadth of partnerships with federal labs (NIST, NSA, NRL) and private industry (Microsoft, Google, Amazon), creating internship and placement pipelines that are notably strong. The location—just outside Washington, D.C., and a 45-minute drive from Baltimore's biomedical corridor—opens pathways to government research roles, defense contractors, and healthcare tech firms. Graduate outcomes are strong: median salaries are competitive with peer R1 institutions, and students frequently place at FAANG companies, research labs, and startups. For students seeking a program with strong fundamentals, research depth, and proximity to both federal and commercial opportunities, UMD offers a compelling middle ground between smaller state schools and elite private universities.
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
- University of Maryland Institute for Advanced Computer Studies (UMIACS)
- Perception and Robotics Group
- Natural Language Processing Group
Industry Partners
- Microsoft (corporate)
- Google (corporate)
- Amazon (corporate)
- NIST (government)
- NSA (government)
- Naval Research Laboratory (NRL) (government)
Career Outcomes
Median Salary: $NaN.
Notable Faculty
- Furong Huang — Machine learning theory, optimization, neural network training
- Dinesh Manocha — Computer vision, robotics, autonomous systems
- Jordan Boyd-Graber — Natural language processing, machine learning
Accreditations and Certifications
Location Advantages: Proximity to National Institute of Standards and Technology (NIST) for government partnerships30 minutes from Washington, D.C. federal agencies and policy centers45 minutes from Baltimore biomedical and healthcare tech corridorIntegrated partnerships with NSA and Naval Research Laboratory
University of Maryland-Baltimore County — Baltimore, MD
Key Distinction: UMBC's machine learning program uniquely combines hands-on industry capstones with deep pipeline access to defense and intelligence sector employers in the Baltimore-Washington corridor.
Hakia Insight: UMBC's CARTA lab and direct pipeline to Northrop Grumman, Lockheed Martin, and APL means your capstone project isn't a simulation—it's often a real-world anomaly detection or cybersecurity problem that your employer is already paying for elsewhere.
At the doctoral level, UMBC's machine learning program stands out for its tight integration with industry-driven research and a curriculum built around real-world problem-solving. The computer science department emphasizes applied machine learning through core coursework in statistical learning, neural networks, and data mining, complemented by electives in computer vision, natural language processing, and reinforcement learning. What sets this program apart is the emphasis on hands-on capstone projects where students tackle problems from partner organizations in healthcare, finance, and cybersecurity—giving graduates portfolio pieces that directly demonstrate industry readiness. UMBC maintains particularly strong connections to the Baltimore-Washington corridor's defense and intelligence agencies, creating internship pipelines that many peer programs lack. Faculty research spans machine learning for cybersecurity, bioinformatics applications, and human-computer interaction, with opportunities for undergraduates to contribute to peer-reviewed publications. The program also benefits from UMBC's strong track record in diversity and inclusion within STEM, fostering collaborative learning environments. Graduate students in the MS program can specialize in machine learning while maintaining flexibility to cross into robotics or data science tracks, and the option to pursue a thesis or non-thesis path accommodates both research-focused and career-oriented students. For those seeking proximity to government R&D labs and Fortune 500 tech operations, UMBC's location and established recruitment relationships provide distinct advantages.
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 Accelerated Real-Time Analytics (CARTA)
- Cyber Defense Lab
Industry Partners
- Northrop Grumman (corporate)
- Lockheed Martin (corporate)
- Johns Hopkins University Applied Physics Laboratory (government)
Notable Faculty
- Haimonti Dutta — Machine learning for cybersecurity and anomaly detection
- Konstantinos Michmizos — Computational neuroscience and machine learning
Accreditations and Certifications
Location Advantages: Proximity to Baltimore-Washington tech corridorAccess to defense and intelligence sector employers (NSA, APL, Northrop Grumman)Close ties to Johns Hopkins research ecosystem
Capitol Technology University — Laurel, MD
Key Distinction: Unique for situating machine learning within applied cybersecurity and systems engineering, positioning graduates for specialized roles in secure ML systems and threat detection.
Hakia Insight: Capitol Technology's unusual strength lies in embedding ML within applied cybersecurity rather than treating security as an afterthought; graduates emerge as specialists in adversarial robustness and threat detection, a rare profile that defense contractors actively recruit for.
At the doctoral level, capitol's machine learning offerings are tightly integrated with its applied cybersecurity and systems engineering heritage, making it an excellent fit for students targeting roles where ML intersects with security, threat detection, and secure systems design. Rather than treating ML as a standalone discipline, the curriculum positions it within the broader ecosystem of secure software development and adversarial robustness—a focus that increasingly matters as organizations defend against AI-powered attacks. The program combines theoretical foundations with intensive lab work where you'll implement algorithms, experiment with real datasets, and participate in capture-the-flag competitions and security challenges. Located in Maryland's tech corridor near Washington D.C., Capitol leverages proximity to defense contractors, federal agencies, and intelligence community employers who actively recruit graduates for roles blending data science with security clearance-eligible positions. The smaller cohort size means closer faculty mentorship and direct access to professors conducting applied research in AI security and anomaly detection.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Industry Partners
- U.S. Department of Defense (government)
- Booz Allen Hamilton (corporate)
Career Outcomes
Top Employers: Booz Allen Hamilton, CACI International, Raytheon Technologies.
Location Advantages: Proximity to Washington D.C. defense and intelligence sectorsAccess to federal contractor employer network
Morgan State University — Baltimore, MD
Key Distinction: Morgan State emphasizes machine learning applications in healthcare, social impact, and government, with mentorship-rich training and ethical AI foundations.
Hakia Insight: Morgan State's doctoral program channels underrepresented talent into leadership roles at APL and NSA where mentorship-rich training has already normalized ethical AI frameworks, creating a cohort effect that shifts institutional culture rather than individual compliance.
At the doctoral level, morgan State's machine learning initiatives align with the university's mission to serve underrepresented populations in STEM and build talent pipelines into tech careers. The program emphasizes foundational machine learning theory alongside applications in healthcare, environmental science, and social impact computing—areas where Morgan faculty have demonstrated research strength. Students benefit from relatively small cohort sizes and direct faculty mentorship, a contrast to larger research universities where graduate students can become anonymous. Morgan's location in Baltimore positions graduates near growing tech corridors and provides partnership opportunities with Johns Hopkins University, the National Security Agency, and regional technology companies. The curriculum integrates ethics and fairness in machine learning, reflecting institutional commitment to responsible AI development. Research opportunities often center on applied problems: predictive health analytics, climate data modeling, and computational social science. While Morgan's machine learning program is still developing its research infrastructure compared to R1 institutions, the university's investment in computing facilities and faculty recruitment in AI signifies institutional priority. Graduates frequently transition into roles at federal research centers, healthcare technology firms, and government agencies, where diversity and contextual problem-solving skills are increasingly valued. The supportive environment and emphasis on both rigor and equity create a distinctive path for students committed to machine learning careers with broader societal impact.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Industry Partners
- Johns Hopkins University Applied Physics Laboratory (government)
- National Security Agency (government)
Career Outcomes
Top Employers: Johns Hopkins APL, National Security Agency, Booz Allen Hamilton.
Location Advantages: Baltimore proximity to Johns Hopkins, APL, and NSAConnections to federal research and intelligence agencies
