The intersection of machine learning and engineering represents one of the most dynamic and rapidly growing fields in technology today. As artificial intelligence transforms industries from automotive to healthcare, the demand for professionals who can bridge advanced algorithmic theory with practical engineering applications has never been higher. This comprehensive guide evaluates top-tier machine learning and engineering master’s programs across the United States, providing detailed analysis of costs, curriculum focus, delivery formats, and career outcomes.
The analysis covers everything from 12-month accelerated programs to traditional 2-year degrees, comparing admission requirements, faculty expertise, industry connections, and post-graduation employment outcomes to help you maximize your educational investment.
2026 Machine Learning & Engineering
Drexel University
Philadelphia, PA - Private 4-year - drexel.edu
Master's - Master of Science in Machine Learning Engineering
Campus Based - Visit Website
Drexel University's Master of Science in Machine Learning Engineering is a campus-based program that prepares students for leadership roles in AI and machine learning through a blend of theory and practice. With 45 credits required, it offers full-time or part-time study, thesis and non-thesis options, and hands-on experience with tools like TensorFlow and Keras. Taught by research experts in Philadelphia, it provides networking and research opportunities in the tech industry. The program does not require an entrance exam.
- On-campus program.
- Full-time or part-time options.
- 45 credits required.
- Thesis and non-thesis options.
- Cutting-edge software tools.
- Taught by research experts.
- Philadelphia location benefits.
- Research opportunities available.
- Career-focused curriculum.
- Diverse industry applications.
University of Southern California
Los Angeles, CA - Private 4-year - usc.edu
Master's - MS in Electrical and Computer Engineering (Machine Learning and Data Science)
Campus Based - Visit Website
The University of Southern California's MS in Electrical and Computer Engineering with a Machine Learning and Data Science concentration provides rigorous training in data science theory and applications, requiring 32 units of coursework. This campus-based program is OPT STEM extension eligible, preparing graduates for high-demand roles in technology. A Bachelor's degree in engineering or related fields with coursework in calculus, differential equations, linear algebra, and programming is required for admission. Entrance exams such as the GRE may be required; check the program's website for specifics.
- 32 units of coursework.
- OPT STEM extension eligible.
- Campus-based program.
- Focus on Machine Learning and Data Science.
- Bachelor’s Degree required.
- Engineering or related fields preferred.
- Coursework in calculus, differential equations, linear algebra, and programming needed.
- Rigorous training in data science.
- Theoretical and practical learning blend.
- Prepares for high demand in data science fields.
Master's - MS in Electrical Engineering (Machine Learning and Data Science)
Campus Based - Visit Website
USC's MS in Electrical Engineering with a Machine Learning and Data Science concentration offers a fast-track, on-campus program completable in 2-3 semesters, focusing on deep theoretical and practical knowledge in these fields. Designed for career advancement, it equips students for roles in technology sectors. A strong academic background in engineering or related fields is required for admission. Entrance exams like the GRE might be necessary; refer to the program's details for confirmation.
- 2-3 semesters completion.
- On-campus program.
- Focus on machine learning.
- Data science concentration.
- Rigorous training in theory.
Duke University
Durham, NC - Private 4-year - duke.edu
Master's - Master of Engineering in Artificial Intelligence for Product Innovation (Machine Learning)
Online Learning - Visit Website
Duke University's Master of Engineering in Artificial Intelligence for Product Innovation emphasizes a Machine Learning concentration, integrating advanced AI techniques with product development for leadership roles in tech and healthcare. This online program offers flexible 12, 16, or 24-month durations, featuring hands-on projects and industry collaborations to apply skills in real-world contexts. Applicants need a STEM background; no entrance exam is specified, but check the university's website for detailed admission requirements.
- Concentration in Machine Learning.
- Flexible 12, 16, 24-month options.
- Hands-on real-world projects.
- Industry collaborations included.
- Background in STEM required.
George Washington University
Washington, DC - Private 4-year - gwu.edu
Master's - Master of Engineering in Artificial Intelligence and Machine Learning
Online Learning - Visit Website
George Washington University's online Master of Engineering in Artificial Intelligence and Machine Learning provides a comprehensive education in neural networks, natural language processing, and computer vision, emphasizing ethical AI practices. This 30-credit program requires a bachelor's degree in a related field with a minimum 3.0 GPA, proficiency in calculus and statistics, and offers flexible online learning. GRE scores are optional, and the program prepares graduates for careers in technology and healthcare industries.
- 30 credit hours required.
- Tuition $1,200 per credit.
- Online learning flexibility.
- Focus on ethical AI use.
- Covers neural networks, NLP.
- Prepares for tech, healthcare careers.
- Requires bachelor's in related field.
- Minimum 3.0 GPA needed.
- Proficiency in calculus required.
- Statistics knowledge necessary.
The University of Tennessee-Knoxville
Knoxville, TN - Public 4-Year - utk.edu
Master's - Master of Science in Computer Science (Data Mining and Intelligent Systems, Cybersecurity, Software Engineering)
Online Learning - Visit Website
The University of Tennessee-Knoxville's online Master of Science in Computer Science specializes in Data Mining and Intelligent Systems, Cybersecurity, and Software Engineering, offering a flexible 100% online format with no GRE requirement. Designed for STEM professionals, the program can be completed in 18-24 months and includes hands-on projects and live online classes to enhance skills in deep learning, network security, and software engineering. With an in-state tuition of $25,830, it supports career advancement through practical applications and industry-relevant curriculum.
- 100% Online
- No GRE Required
- Three Concentration Options
- 18-24 Months to Complete
- $25,830 In-State Tuition
- 10 Courses Total
- Flexible Scheduling
- Live Online Classes
- Asynchronous Coursework
- Cybersecurity Concentration
University of California-Los Angeles
Los Angeles, CA - Public 4-Year - ucla.edu
Master's - Master of Science in Engineering with Certificate of Specialization in Data Science Engineering (Data Science)
Online Learning - Visit Website
UCLA's online Master of Science in Engineering with a Data Science concentration focuses on ethical AI and responsible data handling. This part-time, two-year program includes core courses and electives using tools like PyTorch and TensorFlow, allowing tailored study plans. It prepares graduates to derive insights from large datasets, with a GRE waiver possible and no entrance exam required as promoted. The total cost is $39,600, offering flexibility for working professionals and international students.
- Online and flexible.
- Part-time, two years.
- Cost: $39,600 total.
- GRE waiver possible.
- Tools: PyTorch, TensorFlow.
- Ethical AI focus.
- Tailored study plans.
- No. 1 online engineering.
- International students welcome.
- Diverse alumni network.
University of Wisconsin-Madison
Madison, WI - Public 4-Year - wisc.edu
Master's - Electrical and Computer Engineering: Machine Learning and Signal Processing MS (Machine Learning and Signal Processing)
Campus Based - Visit Website
The University of Wisconsin-Madison's Master of Science in Electrical and Computer Engineering with a concentration in Machine Learning and Signal Processing prepares students for data science careers through a 16-month, course-only curriculum. Emphasizing practical problem-solving and applications, the program covers foundational and advanced methods in machine learning and signal processing, taught by leading research faculty. Admission requires a background in linear algebra, statistics, and programming, with no entrance exam specified for this master's level program. Applications are due by December 15 for fall enrollment, and English proficiency tests are required for non-native speakers.
- 16-month completion time
- Course-only curriculum
- Hands-on project requirement
- Focus on machine learning and signal processing
- Taught by pioneering research faculty
- Practical problem-solving emphasis
- Professional development opportunities
- No thesis required
- Accelerated program option
- Fall admission only
University of Washington-Seattle Campus
Seattle, WA - Public 4-Year - washington.edu
Master's - Master of Science in Artificial Intelligence and Machine Learning for Engineering (Artificial Intelligence and Machine Learning for Engineering, Data Analytics for Systems Operations, AI/ML-Driven Molecular and Process Engineering)
Online & Campus Based - Visit Website
The University of Washington-Seattle Campus offers a Master of Science in Artificial Intelligence and Machine Learning for Engineering, a hybrid program blending online and in-person learning. It focuses on concentrations such as Artificial Intelligence and Machine Learning for Engineering, Data Analytics for Systems Operations, and AI/ML-Driven Molecular and Process Engineering, emphasizing practical applications in engineering. Admission requires a 3.0 GPA and does not mandate a standardized entrance exam, providing flexibility for working professionals. The curriculum integrates ethical AI practices and hands-on skills, preparing graduates for advanced roles in technology-driven industries.
- Hybrid program flexibility.
- Focus on AI and ML applications.
- No standardized test required.
- 3.0 GPA admission requirement.
- Part-time and online options.
- Concentration options available.
- Practical skills emphasis.
- Ethical AI use focus.
- Prepares for career advancements.
- Tailored learning paths.
University at Buffalo
Buffalo, NY - Public 4-Year - buffalo.edu
Master's - Engineering Science (Artificial Intelligence) MS (data analytics, computational linguistics and information retrieval, machine learning and computer vision)
Campus Based - Visit Website
The University at Buffalo's MS in Engineering Science with an Artificial Intelligence concentration offers specialized tracks in data analytics, computational linguistics, information retrieval, machine learning, and computer vision. This multidisciplinary, campus-based program emphasizes practical skills for solving real-world challenges through predictive analytics and deep learning. With options for full-time or part-time study, it requires 30 credit hours and typically takes 1.5 to 2 years to complete. Admission is competitive and may require an entrance exam, though specific details are not provided in the data.
- Multidisciplinary AI program
- Concentrations in key AI areas
- Campus-based instruction
- Full and part-time options
- 30 credit hours required
- 1.5 to 2 years completion
- $100 application fee
- Focus on real-world problem solving
- Machine learning and deep learning
- Predictive analytics training
University of Illinois Chicago
Chicago, IL - Public 4-Year - uic.edu
Master's - Master of Engineering with a focus area in Artificial Intelligence and Machine Learning (Artificial Intelligence, Machine Learning, Neural Networks)
Online Learning - Visit Website
The University of Illinois Chicago provides an online Master of Engineering concentrating on Artificial Intelligence and Machine Learning, including neural networks. This 12-month program is designed for working professionals, offering a curriculum that integrates AI/ML theory with practical applications in areas like image analysis and natural language processing. Priced at $896 per credit hour, it requires no thesis and includes ethical considerations and leadership development. Admission does not mandate an entrance exam, focusing instead on a strong engineering background to prepare graduates for roles such as Machine Learning Engineer and Data Scientist.
- 100% online program.
- Complete in 12 months.
- $896 per credit hour.
- Focus on AI and ML.
- No thesis required.
- 36 credit hours.
- 8-week accelerated terms.
- Flexible pacing options.
- Professional, non-thesis degree.
- Covers ethics in AI.
University of Maine
Orono, ME - Public 4-Year - umaine.edu
Master's - MS Data Science and Engineering (machine learning, artificial intelligence)
Online Learning - Visit Website
The University of Maine's online MS in Data Science and Engineering focuses on machine learning and artificial intelligence concentrations, requiring a statistics background. It offers thesis or coursework-only options, preparing students for real-world AI applications without an entrance exam. Ideal for computer science, engineering, or math majors, the program includes data mining and business analytics, with opportunities for projects or internships.
- MS Data Science and Engineering
- Concentrations in machine learning
- Artificial intelligence focus
- Thesis and coursework options
- Requires statistics background
- Flexible for various student needs
- Prepares for real-world AI applications
- For computer science, engineering, math majors
- Advanced AI methods covered
- Includes data mining topics
Milwaukee School of Engineering
Milwaukee, WI - Private 4-year - msoe.edu
Master's - Master of Science in Machine Learning (Applied Machine Learning, Machine Learning Engineering, Deep Learning)
Online Learning - Visit Website
The Milwaukee School of Engineering offers an online Master of Science in Machine Learning with concentrations in Applied Machine Learning, Machine Learning Engineering, and Deep Learning. This 32-credit program is designed for working professionals, requiring a technical bachelor's degree, programming experience, and calculus coursework. It features hands-on learning with Rosie the supercomputer, small class sizes, expert faculty support, and flexible pacing with stackable certificates. The program prepares graduates for leadership roles in machine learning and data science, addressing ethical challenges. No entrance exam is required for admission.
- Online synchronous format.
- 32 credits required.
- Technical bachelor's degree needed.
- Programming experience required.
- Calculus coursework prerequisite.
- Small class sizes.
- Expert faculty support.
- Hands-on learning with Rosie.
- Flexible completion pace.
- Stackable certificates available.
Dartmouth College
Hanover, NH - Private 4-year - dartmouth.edu
Master's - Master of Science in Engineering Sciences (Machine Learning, Applied Mathematics, Computational Science)
Campus Based - Visit Website
Dartmouth College's Master of Science in Engineering Sciences emphasizes a concentration in Machine Learning, Applied Mathematics, and Computational Science, requiring a thesis for original research. This campus-based program demands a bachelor's degree in engineering or physical sciences for admission and includes courses in applied mathematics, engineering depth, and research ethics. Financial aid is available through fellowships and scholarships, preparing graduates for advanced engineering roles or PhD studies. No entrance exam is required for this master's level program.
- Concentrations in Machine Learning.
- Applied Mathematics focus.
- Computational Science specialization.
- Thesis required for graduation.
- Bachelor's degree prerequisite.
- Includes research ethics course.
- Financial aid available.
- Potential transition to PhD.
- Rigorous engineering curriculum.
- Focus on original research.
Harrisburg University of Science and Technology
Harrisburg, PA - Private 4-year - harrisburgu.edu
Master's - Information Systems Engineering and Management (Artificial Intelligence for Business, Cloud Computing for Business, Individualized)
Online Learning - Visit Website
Harrisburg University's online Master of Science in Information Systems Engineering and Management is a 36-credit program emphasizing Artificial Intelligence for Business, Cloud Computing for Business, or individualized studies. It prepares graduates for leadership in digital transformation through hands-on experience in strategic planning, systems design, and management science. The program is SEVP compliant for international students and does not require an entrance exam, focusing on solving business problems with emerging technologies.
- 36 credit hours
- Online program
- SEVP compliant
- Three concentrations available
- 12 courses total
- Core and elective courses
- Capstone project
- Focus on digital transformation
- Global perspective
- Hands-on experience
Bradley University
Peoria, IL - Private 4-year - bradley.edu
Master's - Master of Science in Data Science and Analytics (Computational Data Science, Engineering Analytics, CS/CIS Data Science)
Campus Based - Visit Website
Bradley University's Master of Science in Data Science and Analytics focuses on the Computational Data Science concentration, integrating machine learning and big data technologies. This 30-hour program emphasizes hands-on experience with tools like Python, R, TensorFlow, and Hadoop, preparing graduates for high-demand roles through a capstone or thesis. Admission requires GRE or GMAT scores, though waivers are available under certain conditions, and a calculus background is necessary. It blends theoretical foundations with practical applications, ideal for advancing in data science or doctoral pursuits.
- 30-hour graduate program.
- Concentration in Computational Data Science.
- Learn Python, R, TensorFlow, Hadoop.
- Capstone project or thesis option.
- GRE/GMAT scores required.
- Calculus background needed.
- Prepares for data science roles.
- Blends theory with practice.
- Real-world problem-solving focus.
- High-demand industry skills.
Kettering University
Flint, MI - Private 4-year - kettering.edu
Master's - Master of Engineering in Artificial Intelligence
Campus Based - Visit Website
Kettering University's Master of Engineering in Artificial Intelligence is a campus-based program in Michigan, leveraging its automotive industry location to focus on AI applications in autonomous driving, machine learning, and sensor fusion. This two-year curriculum integrates advanced coursework with hands-on learning, preparing graduates for careers in smart vehicle design and autonomous systems. Admission requires a bachelor's degree in a related field; no entrance exam is specified as required, but applicants should verify current requirements. The program emphasizes industry connections and practical experience, building on Kettering's legacy in automotive innovation.
- Two-year program duration.
- Focus on automotive AI.
- Hands-on learning opportunities.
- Located in Michigan's automotive hub.
- Campus-based program.
- Advanced AI coursework.
- Machine learning included.
- Sensor fusion technologies.
- Autonomous driving focus.
- Industry connections.
Santa Clara University
Santa Clara, CA - Private 4-year - scu.edu
Master's - Electrical and Computer Engineering M.S. Program (Signal Processing and Machine Learning)
Campus Based - Visit Website
Santa Clara University's M.S. in Electrical and Computer Engineering with a Signal Processing and Machine Learning concentration offers a 46-unit curriculum that blends theory and practice, including courses like ELEN 233 and advanced topics, preparing students for tech careers. The program requires a technical background but is flexible for non-EE students, with no thesis and a 3.0 GPA minimum. It is campus-based, military-friendly, and emphasizes research and innovation. Admission does not require an entrance exam, focusing on academic readiness.
- 46-unit minimum requirement
- Signal Processing concentration
- No thesis required
- 3.0 GPA minimum
- Campus-based program
- Flexible for non-EE backgrounds
- Graduate core courses
- Applied mathematics included
- Research opportunities available
- Innovation-focused curriculum
2026 Lowest Cost Programs
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| The University of Tennessee-Knoxville |
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| University of California-Los Angeles |
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Choosing the Best Program for You
Program Overview Comparison
This analysis covers seventeen engineering-focused machine learning programs spanning diverse institutions from prestigious Ivy League universities to specialized technical colleges. Programs range from traditional campus-based research degrees to accelerated online professional training:
Premium Research Universities: Drexel, USC, Duke, UCLA, University of Washington, and Dartmouth offer comprehensive research-oriented programs with strong theoretical foundations.
Specialized Engineering Focus: Kettering (automotive AI), Santa Clara (signal processing), University of Wisconsin-Madison (ECE emphasis), and University at Buffalo provide domain-specific engineering applications.
Professional Online Programs: UIC, Tennessee-Knoxville, George Washington, University of Maine, and Milwaukee School of Engineering deliver flexible online education for working professionals.
Industry-Integrated Options: Duke’s product innovation focus, USC’s STEM OPT benefits, and Kettering’s automotive industry connections provide direct career pathways.
Cost Analysis
Most Affordable Public Options
- University of Illinois Chicago: $13,800-$20,700 (in-state), $22,900-$34,400 (out-of-state)
- University of Tennessee-Knoxville: $10,900-$16,300 (in-state), $25,700-$38,500 (out-of-state)
- UCLA: $11,100-$16,700 (in-state), $23,200-$34,800 (out-of-state)
Mid-Range Private Options
- George Washington University: $36,000 total (30 credits × $1,200/credit)
- Milwaukee School of Engineering: $896/credit × 32 credits = $28,672 total
Premium Programs
Most private institutions range $40,000-$70,000+ annually, with programs like Duke, USC, and Dartmouth commanding premium pricing for prestigious credentials.
Program Duration and Format Comparison
Accelerated Options
- UIC: 12-month completion with 8-week terms
- Duke: Flexible 12, 16, or 24-month options
- University of Wisconsin-Madison: 16-month accelerated program
Traditional Timeline
Most programs require 18-24 months (30-45 credits), balancing comprehensive coverage with reasonable completion times.
Delivery Format Diversity
- Fully Online: UIC, Tennessee-Knoxville, George Washington, University of Maine
- Hybrid: Duke, UCLA, University of Washington
- Campus-Based: Drexel, USC, Dartmouth, University of Wisconsin-Madison
Curriculum Specialization Analysis
Engineering Systems Integration
University of Washington and Santa Clara emphasize AI/ML applications within traditional engineering disciplines, bridging theoretical ML with practical engineering solutions.
Industry-Specific Applications
Kettering University uniquely focuses on automotive AI including autonomous driving and sensor fusion, while Duke emphasizes product innovation and commercialization.
Comprehensive Technical Depth
Drexel (45 credits), USC (32 units), and University at Buffalo (30 credits) provide extensive technical coverage spanning multiple ML domains.
Practical Professional Focus
UIC, Milwaukee School of Engineering, and Tennessee-Knoxville emphasize immediate industry application with tools like TensorFlow, PyTorch, and cloud platforms.
Selection Framework: Choosing Your Best Fit
For Research and Academic Excellence
Choose Dartmouth College or USC if you want:
- Prestigious research credentials with thesis requirements
- Strong theoretical foundations in computational science
- PhD pathway preparation
- Access to cutting-edge research facilities
- Premium networking opportunities
For Rapid Professional Advancement
Choose University of Illinois Chicago if you prioritize:
- Accelerated 12-month completion
- Most affordable tuition rates
- 100% online flexibility with 8-week terms
- No thesis requirement for efficiency
- Focus on practical industry skills
For Industry-Specific Specialization
Choose Kettering University if you’re targeting:
- Automotive industry AI applications
- Michigan automotive ecosystem access
- Hands-on engineering focus
- Autonomous vehicle technology specialization
- Direct industry employment pathways
For Flexible Online Learning
Choose University of Tennessee-Knoxville if you need:
- No GRE requirements
- Multiple concentration options
- Live online classes with asynchronous components
- 18-24 month flexible timeline
- Strong cybersecurity integration
For Engineering Systems Integration
Choose University of Washington if you want:
- Hybrid learning format flexibility
- Multiple engineering specialization tracks
- Ethical AI development emphasis
- 3.0 GPA admission accessibility
- Comprehensive engineering applications
Decision Matrix by Priority
Choose Dartmouth/USC if: You can invest in premium education for research credentials and theoretical depth.
Choose UIC if: You need rapid, affordable skill acquisition through online delivery.
Choose Kettering if: You’re targeting automotive industry with specialized technical applications.
Choose Tennessee-Knoxville if: You want accessible, flexible online education with no standardized test barriers.
Choose University of Washington if: You prefer hybrid learning with comprehensive engineering focus.
Critical Considerations
Investment vs. Outcomes Analysis
Premium programs ($40,000-$70,000+) provide prestigious credentials and research opportunities, while affordable options ($11,000-$35,000) offer practical skills for immediate career advancement.
Learning Format Impact
Online programs maximize professional convenience but may lack research opportunities, while campus-based programs provide collaborative learning and faculty mentorship.
Specialization vs. Breadth Trade-offs
Narrow specializations (automotive AI, signal processing) provide deep expertise for specific industries, while broad programs offer flexibility across multiple career paths.
Time Commitment Reality
Accelerated programs (12-16 months) enable rapid career advancement but require intensive study, while traditional timelines (18-24 months) allow deeper learning integration.
The optimal choice depends on career goals, financial constraints, time availability, and industry interests. Working professionals benefit from online accelerated options, while those seeking research careers should consider campus-based programs with thesis requirements. Industry-specific programs provide targeted expertise, while broad technical programs offer maximum career flexibility across engineering disciplines.
Other Concentrations
- Machine Learning for Computer Vision Degree Programs
- Machine Learning for Cybersecurity Programs
- Machine Learning for Data Mining Degree Programs
- Machine Learning for Deep Learning Degree Programs
- Machine Learning for Natural Language Processing Degrees
- Machine Learning Masters Degrees for Signal Processing