Masters in Machine Learning Schools

Johns Hopkins University's online Master of Science in Artificial Intelligence is tailored for professionals seeking to excel in AI, blending machine learning, natural language processing, and robotics into a curriculum that balances theory with practical application. Designed by leading researchers, the program empowers students to drive innovation in AI technologies. Its flexibility allows for personalized study paths, accommodating working professionals. Admission is open to those with a bachelor's degree, with applications accepted throughout the year. The program is noted for its potential for employer tuition support, making it an accessible option for many. No entrance exam is specified, focusing instead on academic and professional qualifications.

• Online program format
• Covers AI, machine learning
• Flexible course options
• Year-round applications
• Employer tuition contributions
• Bachelor's degree required
• Practical and theoretical focus
• Top researchers as instructors
• Innovation in AI technologies
• Tailored study options

Drexel University's Master of Science in Machine Learning Engineering is a comprehensive program designed to prepare students for leadership roles in AI and machine learning. It offers a blend of theoretical knowledge and practical skills, with courses covering core machine learning concepts, mathematical theory, and electives for specialization. Students can choose between thesis and non-thesis options, catering to those interested in further academic research or industry careers. The program is taught by experts and provides hands-on experience with modern tools like TensorFlow and Keras. Located in Philadelphia, it offers unique networking and research opportunities in a thriving tech environment. No entrance exam is required for admission.

• 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.

The Master of Science in Artificial Intelligence and Machine Learning at Drexel University focuses on applied and computational tracks, offering students a deep understanding of AI and ML technologies. This program is designed for flexibility, with full-time or part-time study options and the choice between on-campus or online formats. A bachelor's in computer science or a related STEM field is required for the computational track. The curriculum includes a capstone project for practical experience, and the program operates on a quarter system, requiring 45 credits for completion. Scholarships and financial aid are available. No entrance exam is required for admission.

• Top 10 AI program
• Applied and computational tracks
• Full-time or part-time
• On campus or online
• 45 credits required
• Capstone project included
• STEM designated
• Quarter system curriculum
• Scholarships available
• Hands-on experience

Drexel University offers an online Master of Science in Artificial Intelligence & Machine Learning with concentrations in Data Science and Analytics, Theory of Computation and Algorithms, and Applications of AI/ML. This program is tailored for professionals seeking to advance their skills in AI and ML, using state-of-the-art tools to solve real-world problems. The 45-quarter credit program is flexible, with full- or part-time options, and requires a strong background in computer science. Tuition is $1438 per credit, with financial aid options available. Admission requires a bachelor's degree, a 3.0 GPA, and submission of relevant documents. GRE scores are recommended but not required for some applicants.

• 45-quarter credit program.
• Concentrations in Data Science, Algorithms, AI/ML.
• Online format for flexibility.
• $1438 per credit tuition.
• Financial aid available.
• Requires strong computer science background.
• Capstone project included.
• Full- or part-time options.
• 10-week quarter terms.
• Interdisciplinary curriculum.

The University of Massachusetts-Amherst offers a specialized M.S. Concentration in Artificial Intelligence and Machine Learning Systems, designed to provide students with an in-depth understanding of AI and ML technologies. This campus-based program emphasizes a comprehensive curriculum that includes five specialized courses, ranging from image processing to neural networks, ensuring a blend of theoretical knowledge and practical lab experience. Tailored for individuals from various academic backgrounds, it prepares graduates for both research and professional careers in the rapidly evolving AI/ML field. Admission is contingent upon meeting the Electrical and Computer Engineering MS degree requirements, with no mention of an entrance exam requirement, highlighting the program's accessibility to aspiring AI/ML professionals.

• Focus on AI/ML Systems.
• Campus-based program.
• Five specialized courses required.
• Lab components included.
• Prepares for research or professional roles.
• Admission based on MS degree criteria.
• Covers image processing to neural networks.
• Blends theory with practical experience.
• For students from diverse backgrounds.
• Focus on both hardware and software.

The University of Florida's Master of Science in Artificial Intelligence Systems stands out for its interdisciplinary approach, combining computer science, mathematics, engineering, and ethics to prepare students for the evolving AI landscape. With a 30-credit curriculum that includes core courses, electives, and a capstone project, students gain hands-on experience using the HiPerGator supercomputer. This program is ideal for those aiming to make an impact in IT, healthcare, or finance, emphasizing both technical skills and ethical AI development. Admission is competitive, requiring a related bachelor's degree, but no entrance exam is specified. The campus setting enhances learning with direct access to resources and a focus on practical applications.

• 30 credit hours
• Interdisciplinary curriculum
• HiPerGator supercomputer access
• Capstone project included
• Campus-based program
• Focus on ethics in AI
• Prepares for IT, healthcare, finance careers
• Bachelor's degree required for admission

The University of Central Florida's Master of Science in Data Analytics with an Artificial Intelligence Track is a hybrid program blending online and in-person learning. This 30-credit hour program is designed for professionals aiming to specialize in AI, focusing on algorithm design, machine learning, and data interpretation. It emphasizes practical skills through a semester-long project, preparing graduates for roles such as AI Analyst or Machine Learning Engineer. With a total cost of $36,300, the program is structured over five intensive semesters and requires a STEM background, offering a pathway for further Ph.D. studies. It addresses the increasing demand for AI expertise across various sectors.

• 30 credit hour program
• Hybrid learning format
• Focus on AI and data analytics
• No thesis required
• Semester-long project included
• Prepares for AI Analyst roles
• Opportunity for Ph.D. advancement
• $36,300 total cost
• Requires STEM background
• Intensive 5-semester schedule

Carnegie Mellon University's Master of Science in Machine Learning stands out as a rigorous 16-month campus program, blending 6 core courses with 3 electives and a practicum for hands-on experience. Tailored for those with a solid foundation in computer science and mathematics, it emphasizes probability, statistics, and programming. Notably, GRE scores are optional for 2025 applicants, and the program's STEM designation offers enhanced career prospects in AI and data science. While financial support isn't available, the program's comprehensive curriculum and post-graduate career support make it a top choice for aspiring machine learning professionals.

• 16-month program duration
• Campus-based learning
• 6 core courses required
• 3 elective courses
• Practicum component
• Strong math background needed
• Programming skills essential
• No financial support
• GRE optional for 2025
• STEM-designated program

The Master's in Machine Learning - Applied Study at Carnegie Mellon University is a 16-month, campus-based program designed for students targeting industry roles. It combines 6 core courses and 3 electives with a mandatory internship, focusing on practical machine learning applications. A strong background in computer science and mathematics is required, with programming skills in Python or Java being beneficial. This STEM-designated program does not offer financial support but enhances visa options for international students. Admissions are competitive, with a December deadline for an August start, making it ideal for those seeking to apply machine learning in real-world settings.

• 16-month program duration.
• Campus-based learning.
• STEM-designated program.
• Mandatory internship included.
• 6 core courses required.
• 3 elective courses.
• Professional development activities.
• Strong CS and math prerequisites.
• Programming skills in Python/Java.
• No financial support provided.

Carnegie Mellon University's 5th-Year Master's in Machine Learning offers CMU undergraduates a unique opportunity to earn an MS in just one additional year. This program allows double-counting up to three courses towards both degrees, featuring core and elective courses plus a practicum. Admission is competitive, requiring a CMU bachelor's degree, completion of specific courses with a B or better, and submission of a statement of purpose, resume, academic records, mid-semester grades, and two letters of recommendation. No GRE is required, and the program is designed for full-time study, providing a fast track to advanced machine learning expertise.

• One-year program duration.
• Double-count up to three courses.
• Full-time study required.
• Campus-based program.
• Practicum included.
• Competitive admissions.
• No GRE scores required.
• Two letters of recommendation.
• Statement of purpose needed.
• Mid-semester grades submission.

The University of Arizona offers a Master of Science in Information Science with a specialized concentration in Machine Learning, designed for students aiming to lead in the rapidly evolving field of data science. This STEM-designated program, located in Tucson, AZ, emphasizes practical skills through a curriculum that includes a capstone project or internship, preparing graduates for high-demand careers. With the potential to complete the program in just 18 months and an impressive average graduate salary of $98K, it stands out for its efficiency and return on investment. The program requires 30 academic credits and caters to both in-state and out-of-state students, with admissions following specific deadlines. Notably, the program does not explicitly require an entrance exam, making it accessible to a broader range of applicants.

• STEM-designated program
• Concentration in Machine Learning
• On-campus in Tucson, AZ
• Complete in 18 months
• 30 academic credits required
• Capstone project or internship
• Average salary $98K
• In-state and out-of-state tuition options
• Specific admissions deadlines
• Focus on data science

The University of Texas at Austin's online Master's in Artificial Intelligence program is tailored for aspiring AI professionals, with a strong emphasis on Machine Learning, Natural Language Processing, and Computer Vision. This 30-hour, 10-course curriculum delves into deep learning and AI ethics, preparing students for the burgeoning global AI job market. Priced at around $10,000, it stands out as a cost-effective choice for quality education. The program's online format offers unparalleled flexibility, accommodating students from various time zones. Admission requires a bachelor's degree, with applications accepted for Fall and Spring terms. Notably, the program does not mandate an entrance exam, making it accessible to a broader audience.

• 100% online program.
• Focus on Machine Learning.
• Covers Natural Language Processing.
• Includes Computer Vision.
• Affordable $10,000 tuition.
• Flexible asynchronous courses.
• World-class faculty.
• 30-hour program.
• 10 courses to graduate.
• Ethics in AI required.

The University of Tennessee-Knoxville's online Master of Science in Computer Science program stands out for its focus on Data Mining and Intelligent Systems, Cybersecurity, and Software Engineering. Tailored for STEM professionals aiming to deepen their expertise in cutting-edge computer science fields, this program offers a comprehensive curriculum covering deep learning, network security, and more. Notably, it requires no GRE for admission, making it accessible to a broader range of applicants. With an estimated in-state tuition of $25,830 and the flexibility of 100% online coursework, students can graduate in 18 to 24 months. The program's structure supports working professionals through live online classes, asynchronous coursework, and multiple start dates throughout the year.

• 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

Indiana University-Bloomington's M.S. in Computer Science with a Machine Learning concentration is tailored for those seeking to lead in the tech sector. This rigorous program merges core computer science principles with specialized knowledge in AI and data analytics, equipping students for lucrative careers. Typically completed in 1.5 to 2 years, it emphasizes practical learning through internships and collaborative research, supported by a faculty renowned for their expertise. Graduates enjoy a 100% employment rate, with starting salaries averaging $126,067. A solid computer science background is required for admission, and financial assistance is accessible for qualified candidates. The GRE is not explicitly mentioned as a requirement, suggesting a holistic review process.

• Concentration in Machine Learning
• 1.5 to 2 years completion
• Campus-based program
• High employment rate
• Average salary $126,067
• Internship opportunities
• Research with faculty
• Financial aid available
• Strong industry connections
• Cutting-edge curriculum

Northeastern University's Master of Science in Artificial Intelligence program, specializing in Machine Learning, stands out for its rigorous 32-credit curriculum that merges theoretical foundations with hands-on applications in data science, deep learning, and robotics. Situated in Boston, MA, students benefit from a dynamic academic setting, state-of-the-art research labs, and strong industry ties. The program emphasizes practical skills and innovation, preparing graduates for leadership roles in AI. With options for financial aid and co-op experiences, it supports students in achieving both academic and professional success. Admission is competitive, requiring a demonstration of academic prowess and a passion for advancing AI technologies. No entrance exam is specified, highlighting a holistic review process.

• 32 credit hours required
• Concentration in Machine Learning
• Campus-based program
• Located in Boston, MA
• Financial aid available
• Co-op opportunities
• Cutting-edge research facilities
• Industry connections
• Comprehensive AI curriculum
• Practical applications focus

The University of Utah offers a Professional Science Master's in Computational & Data Science with a Machine Learning concentration, tailored for individuals with a robust quantitative foundation. This program uniquely combines algorithm development, machine learning techniques, and statistical inference through hands-on, interdisciplinary projects. Designed for flexibility, it allows full-time students to graduate in 2 years, with part-time options extending up to 4 years. Applicants must demonstrate proficiency in calculus, linear algebra, and programming, alongside maintaining a GPA above 3.0. The 36-credit curriculum not only delves into computational and statistical methodologies but also incorporates essential business skills and a capstone professional project, preparing graduates for thriving careers in data science and machine learning. No entrance exam is required for admission.

• Concentration in Machine Learning.
• Full-time completion in 2 years.
• Part-time options available.
• 36 credits required.
• GPA higher than 3.0 needed.
• Strong quantitative background prerequisite.
• Includes professional experience project.
• Blends theory with practical projects.
• Covers algorithm development.
• Focus on statistical inference.

The University of Oklahoma-Norman Campus offers an online Master of Science in Computer Science with a concentration in Machine Learning, tailored for professionals aiming to excel in the rapidly evolving tech industry. This 33-credit program, achievable in 21 months, emphasizes artificial intelligence and data mining, equipping students with the skills needed for high-demand careers. Unique for its no GRE requirement, the program seeks applicants with a related bachelor's degree and a 3.0 GPA. Its fully online format combines asynchronous and live classes, ensuring flexibility and accessibility for students worldwide. This program stands out for its focus on advanced computer science topics and its commitment to preparing graduates for the forefront of technology innovation.

• 33-credit program
• Completed in 21 months
• Fully online format
• Machine Learning concentration
• No GRE required
• 3.0 GPA requirement
• Related bachelor's degree needed
• Blend of async and live classes
• Covers AI, data mining
• Prepares for tech careers

The University of Wisconsin-Whitewater offers a Master of Science in Computer Science designed to equip students with advanced skills in software systems, AI, big data, and cybersecurity. This 30-credit program stands out for its project-oriented approach, allowing students to apply theoretical knowledge to real-world challenges. With affordable tuition and flexible curriculum paths, it caters to a wide range of educational backgrounds, ensuring graduates are well-prepared for high-demand tech roles. Admission is based on a personal statement, references, and completion of prerequisite undergraduate courses, with considerations for relevant professional experience. Notably, the program does not require an entrance exam, making it accessible to a broader audience.

• 30-credit program.
• Project-oriented education.
• Affordable tuition rates.
• Personalized curriculum paths.
• Strong career outcomes.
• Diverse faculty expertise.
• On-campus and online options.
• Focus on current tech trends.
• Admissions flexibility.
• High earning potential.

Duke University's Master of Engineering in Artificial Intelligence for Product Innovation, with a concentration in Machine Learning, is designed for professionals seeking to lead in the AI-driven future. This online program uniquely combines machine learning expertise with product innovation, ideal for those targeting careers in technology, healthcare, and beyond. With flexible completion options of 12, 16, or 24 months, it accommodates varying schedules. The curriculum emphasizes practical experience through hands-on projects and industry partnerships, ensuring graduates are ready to tackle real-world challenges. A STEM background is required for admission, aligning with the program's technical rigor. Duke's prestigious reputation and Methodist affiliation underscore its commitment to excellence and service.

• Concentration in Machine Learning.
• Flexible 12, 16, 24-month options.
• Hands-on real-world projects.
• Industry collaborations included.
• Background in STEM required.

The University of Texas at Dallas offers a Master of Science in Computer Science with a focused concentration in Artificial Intelligence (AI), Machine Learning, and Data Science. This program is designed for those aiming to excel in the rapidly evolving tech sector, offering a curriculum that merges theoretical knowledge with hands-on experience. Students will engage with esteemed faculty and have access to cutting-edge research opportunities, all while being situated near Dallas's thriving technology hub. Applicants must possess a bachelor's degree, demonstrate proficiency in programming, calculus, and linear algebra, and submit GRE scores. The program's flexibility accommodates both full-time students and professionals seeking to advance their careers.

• Concentration in AI, Machine Learning
• Campus-based program
• Flexible class schedules
• Strong industry connections
• Research opportunities available
• Requires GRE scores
• Bachelor's degree prerequisite
• Strong programming foundation needed
• Renowned faculty
• Multidisciplinary approach

Columbia University's online MS in Computer Science with a Machine Learning concentration offers a rigorous curriculum designed for tech professionals aiming to specialize in AI and data analysis. This program stands out for its flexibility, allowing students to balance studies with work commitments. It delves into advanced topics such as algorithms and statistical modeling, with real-world applications in sectors like finance and bioinformatics. Admission prerequisites include a relevant bachelor's degree, GRE scores, and programming expertise. The program's blend of theoretical knowledge and hands-on projects ensures graduates are well-prepared for the evolving demands of the machine learning field.

• Online MS program.
• Focus on Machine Learning.
• Flexible for professionals.
• Covers AI and data.
• GRE scores required.
• Programming proficiency needed.
• Blends theory and practice.
• Prepares for tech roles.

The University of Akron Main Campus presents an M.S. in Computer Science with a specialized concentration in Artificial Intelligence and Machine Learning, tailored for students seeking advanced knowledge in computing. This campus-based program offers a dynamic curriculum with choices between thesis and non-thesis tracks, accommodating various academic and professional goals. Prospective students must hold a bachelor's degree in a relevant field, demonstrate a minimum GPA of 2.75, and possess strong programming and mathematical skills. Focused on cutting-edge research in AI and ML, the program equips graduates for high-demand positions in the technology sector. Additionally, an accelerated option is available for those eager to expedite their master's journey. Entrance exams are required for admission.

• Flexible curriculum options
• Thesis and non-thesis paths
• Concentration in AI and ML
• Accelerated degree option
• Research-focused faculty
• Requires bachelor's degree
• GPA of 2.75 or higher
• Proficiency in programming needed
• Strong mathematical foundation required
• Prepares for tech industry roles

The University of Rhode Island's online Master of Science in Data Science program is tailored for aspiring data scientists, with a strong emphasis on Machine Learning, Data Visualization and Analytics, and Artificial Intelligence. This program stands out for its comprehensive curriculum that bridges theoretical knowledge with practical application, preparing students to solve complex problems using data. Notably, it does not require a GRE for admission, broadening access for diverse applicants. Prerequisites include proficiency in R and Python, along with foundational knowledge in calculus, linear algebra, and statistics. At $887 per credit, it offers an affordable pathway to mastering data science skills for high-demand careers across industries.

• Online program flexibility
• Focus on Machine Learning
• Data Visualization and Analytics
• Artificial Intelligence concentration
• $887 per credit tuition
• No GRE required
• R and Python programming needed
• Calculus prerequisite
• Linear algebra prerequisite
• Introductory statistics prerequisite

Montana State University offers a Master of Science in Data Science with concentrations in Machine Learning, Artificial Intelligence, and Data Mining. This campus-based program is designed for individuals with a strong background in mathematics, statistics, and computer science, aiming to solve complex data challenges. The 30-credit curriculum blends foundational courses in algorithms and machine learning mathematics with elective options for specialization. Prerequisites include calculus, linear algebra, data structures, and statistics, ensuring students are well-prepared for advanced studies. The program emphasizes real-world problem-solving, advanced statistical methods, and computational techniques, alongside collaborative projects and technical communication skills development. No entrance exam is mentioned as required for admission.

• Interdisciplinary curriculum.
• Focus on Machine Learning.
• 30 credits required.
• Campus-based program.
• Strong prerequisite foundation.
• Flexible specialization options.
• Includes foundational courses.
• Electives in AI.
• Data Mining focus.
• Real-world problem solving.

Long Island University's M.S. in Artificial Intelligence program stands out for its specialized focus on Machine Learning & Pattern Recognition, Data Mining and Exploration, and Applicable Deep Learning. This 30-credit, campus-based program is tailored for students aiming to excel in AI research and development, offering a blend of theoretical foundations and practical applications. With courses such as Programming in Python, Statistical Learning, and Deep Learning, students are equipped with the skills needed for the evolving tech landscape. The program provides flexibility with both course-only and thesis options, alongside access to a state-of-the-art learning center for hands-on experience with the latest technologies. Located in NY, it prepares graduates for successful careers in AI, emphasizing a multidisciplinary approach to learning. Entrance exams may be required for admission.

• 30-credit M.S. program
• Focus on Machine Learning
• Includes Data Mining
• Offers Deep Learning courses
• Course-only and thesis options
• State-of-the-art learning center
• Prepares for AI careers
• Located in NY
• Hands-on technology experience
• Multidisciplinary study approach

DePaul University's online MS in Artificial Intelligence is designed for those aiming to excel in the rapidly evolving field of AI. This program delves into machine learning, natural language processing, robotics, and cognitive science, preparing graduates for roles as AI/ML engineers or research scientists. With a curriculum that spans 48-72 credit hours, it includes foundational courses, advanced electives, and a capstone project, offering a comprehensive education in AI. The program is tailored for working professionals, providing flexibility with its online format. Admission is open to holders of a bachelor's degree, with prerequisites in programming and data structures for non-computer science majors. Notably, DePaul emphasizes a practical approach to AI, blending theory with real-world applications.

• 48-72 credit hours
• Online program available
• Focus on machine learning
• Includes natural language processing
• Covers robotics and cognitive science
• Capstone project required
• Electives in AI topics
• Prepares for AI/ML careers
• Flexible for working professionals
• Admission requires bachelor's degree

The University of Nebraska-Lincoln's Master of Science in Computer Science with a Machine Learning concentration is tailored for those seeking to advance their knowledge in this dynamic area. This program emphasizes both theoretical understanding and practical skills, equipping students for roles in technology innovation and research. It requires a bachelor's degree with computer science prerequisites and is delivered on-campus, providing access to modern research facilities. Notably, the program does not require a GRE for admission but does need a TOEFL score of at least 100 for non-native English speakers. Financial aid is available to support students in their academic journey.

• Concentration in Machine Learning.
• 30 credit hours required.
• On-campus program.
• Thesis and non-thesis options.
• Access to advanced research facilities.
• Minimum TOEFL score of 100.
• No GRE required.
• Three letters of recommendation needed.
• Personal statement required.
• Resume/CV submission.

The University of Houston-Downtown's Master of Science in Artificial Intelligence stands out for its specialized concentrations in Data Mining, Deep Learning, and Natural Language Processing. This 30-credit hour hybrid program is tailored for individuals with a solid foundation in programming and mathematics, offering a unique blend of theoretical and practical AI training. Utilizing Python and TensorFlow, students gain hands-on experience in cutting-edge AI applications. Admission prerequisites include a bachelor's degree, a minimum GPA of 3.0 in the last 60 credit hours, and completion of foundational programming and mathematics courses. Recognized as a top AI program, it provides flexible hybrid learning options, including evening face-to-face courses.

• 30 credit-hour program
• Hybrid learning format
• Concentrations available
• Strong programming focus
• Hands-on AI training
• Python and TensorFlow
• GPA 3.0 requirement
• Foundational courses needed
• Evening face-to-face courses

Harvard University's Master's in Data Science, specializing in Machine Learning, stands out for its rigorous curriculum designed to master statistical modeling and big data analytics. This on-campus program spans at least three semesters, requiring completion of 12 courses, with opportunities for thesis research. Tailored for individuals proficient in calculus, linear algebra, and programming, it fosters expertise in data visualization and ethical data practices. Notably, the program does not mandate an entrance exam, broadening access to a diverse cohort. Financial support through scholarships and teaching fellowships enhances its appeal, preparing graduates for impactful roles across the data science landscape.

• 12 courses required
• 3 semesters minimum
• Machine Learning concentration
• Campus-based program
• No formal prerequisites
• Background in calculus needed
• Programming fluency required
• Interdisciplinary field
• Financial aid available
• Teaching fellowships offered