California Machine Learning Masters Degree Programs

The University of San Diego's online Master of Science in Applied Artificial Intelligence stands out for its comprehensive approach to AI education, blending technical skills with ethical considerations. This 20-month program is tailored for STEM professionals seeking to advance in the AI sector, offering a curriculum rich in machine learning, neural networks, and deep learning. Unique features include a capstone project, live weekly office hours, and teamwork final projects, all designed to apply theoretical knowledge to real-world problems. With a tuition of $965 per unit and no GRE/GMAT requirement for applicants with a GPA above 2.75, it provides an accessible pathway to AI expertise. The program's emphasis on ethics and social good, alongside its flexible online format, makes it a compelling choice for aspiring AI professionals.

• 20-month duration
• Online program
• $965 per unit
• No GRE/GMAT for GPA >2.75
• STEM-focused curriculum
• Ethics and social good emphasis
• Hands-on AI applications
• Flexible learning format
• 30 academic units
• Capstone project required

Golden Gate University offers an innovative MS in Business Analytics with a concentration in Machine Learning for Predictive Analytics, tailored for those aiming to master the art of turning data into actionable insights. This program stands out for its emphasis on practical skills in Python, predictive modeling, and data analytics, all within a flexible learning environment that includes online options. Designed with working professionals in mind, it requires no GMAT or GRE, removing barriers to entry. Located in San Francisco, a hub for tech innovation, the program provides a competitive edge with its career-focused curriculum and hands-on approach to machine learning applications.

• 36 total units
• No GMAT/GRE required
• Hybrid, on campus, online
• Focus on Python and data analytics
• Competitive tuition
• Career-focused curriculum
• Flexible for working professionals
• Located in San Francisco, CA
• Machine Learning concentration
• Practical applications emphasized

The University of California-Los Angeles (UCLA) provides an innovative online Master of Science in Engineering program, specializing in Data Science Engineering, ideal for professionals seeking to advance their expertise in ethical data utilization and responsible AI. This program stands out for its comprehensive curriculum, including five core courses and four electives, enabling personalized learning paths. Students gain proficiency in cutting-edge tools such as PyTorch and TensorFlow, alongside mastering Bayesian Inference techniques. Designed for flexibility, the program accommodates working professionals with its part-time, two-year online format. Admission criteria include submission of transcripts, a resume, recommendation letters, and a personal statement, with a GRE waiver option available. The total program cost is $39,600, offering access to a prestigious education with the convenience of online learning. UCLA's program is recognized for its focus on ethical AI, preparing graduates to extract meaningful insights from vast datasets, supported by a robust alumni network.

• 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.

The University of Southern California's MS in Electrical and Computer Engineering, with a concentration in Machine Learning and Data Science, is designed to meet the growing demand for professionals in these fields. This 32-unit campus program combines rigorous theoretical training with practical applications, focusing on extracting insights from large datasets to drive technological advancements. Eligible for the OPT STEM extension, it's particularly appealing to international students. Applicants must hold a Bachelor’s Degree in engineering or a related field, with prior coursework in calculus, differential equations, linear algebra, and programming. No entrance exam is mentioned, emphasizing a strong academic foundation for admission.

• 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.

At the University of Southern California, the MS in Electrical Engineering offers a specialized concentration in Machine Learning and Data Science, catering to students eager to explore these areas in depth. This on-campus program can be completed in just 2-3 semesters, offering a swift pathway to expertise in machine learning and data science. It's tailored for individuals at any career stage, aiming to equip them with the skills needed for high-demand positions in tech and engineering. A robust academic background in engineering or related disciplines is required for admission, with no specific entrance exam listed, highlighting the program's focus on academic preparedness.

• 2-3 semesters completion.
• On-campus program.
• Focus on machine learning.
• Data science concentration.
• Rigorous training in theory.

San Jose State University offers a Master of Science in Artificial Intelligence with specialized concentrations in Data Science and Autonomous Systems, tailored for students aiming to lead in the AI and machine learning fields. This campus-based program, situated in the heart of Silicon Valley, provides an unparalleled opportunity to engage with cutting-edge technologies and industry leaders. The curriculum is meticulously designed to balance theoretical knowledge with practical application, focusing on predictive analytics, data management, and the development of intelligent systems. Emphasizing ethical considerations and collaborative projects, it prepares graduates for impactful roles in AI. A relevant bachelor's degree is required for admission, with no mention of an entrance exam, making it accessible to a broad range of applicants.

• Concentrations in Data Science.
• Autonomous Systems focus.
• Campus-based program.
• Silicon Valley location.
• Ethical AI emphasis.
• Teamwork and leadership skills.
• Practical and theoretical balance.
• Relevant bachelor's degree required.
• Prepares for AI leadership roles.
• Cutting-edge technology focus.

California State University-Long Beach offers a Master of Science in Information Systems with concentrations in Artificial Intelligence, Cybersecurity, and Business Analytics, tailored for those looking to advance in IT and business sectors. This STEM-designated, 21-month program emphasizes practical skills in Python, AWS, SQL, and Tableau, preparing students for roles in machine learning and data visualization. Designed with working professionals in mind, classes are held evenings and Saturdays. The $31,500 fee covers all textbooks and materials, and notably, no GMAT/GRE is required for admission. The program also provides career services and an extensive alumni network, supporting students' professional growth.

• STEM-designated program
• 21-month duration
• Evening and Saturday classes
• $31,500 program cost
• No GMAT/GRE required
• Python, AWS, SQL, Tableau tools
• Hands-on learning approach
• Textbooks and materials included
• Cohort-model program
• Fall semester start

The University of California-Santa Barbara offers a Master of Science in Computer Science with a concentration in Machine Learning, designed for students aiming to excel in advanced industry positions or academic research. This program stands out for its flexible completion paths, including thesis, project, or comprehensive examination options, catering to a wide range of academic and professional goals. With a requirement of 42 units covering both major and breadth area courses, it ensures a comprehensive understanding of computer science fundamentals, particularly in machine learning. Admission demands a solid background in computer science, underscored by specific grade prerequisites for major courses. Emphasizing research, the program encourages early collaboration with faculty advisors, fostering a rich learning environment. Ideal for students from various scientific disciplines, it combines rigorous coursework with practical research opportunities. Details on costs and applications are readily accessible, accommodating applicants at different stages of their careers. Notably, the program does not explicitly require an entrance exam, making it more accessible to a broader audience.

• Campus-based program.
• Concentration in Machine Learning.
• Three completion options available.
• 42 units of coursework required.
• Strong foundation in CS needed.
• Research emphasis.
• Early faculty advisor engagement.
• Flexible for diverse backgrounds.
• Major and breadth area courses.
• Grade requirements for major courses.

The University of California-Davis offers a Master of Science in Computer Science with a focus on Artificial Intelligence and Machine Learning, Computer Vision, and Data Science. This campus-based program is tailored for students seeking to master cutting-edge technologies through a combination of core and elective courses. Admission prerequisites include a bachelor's degree, a minimum GPA of 3.0, and a strong foundation in computer science. The program is designed to equip students with both practical skills and research experience, preparing them for leadership positions in the technology sector. Notably, the GRE is required for admission, aligning with the program's rigorous academic standards.

• Campus-based program.
• Concentrations in AI, ML, Computer Vision, Data Science.
• Requires bachelor's degree for admission.
• Minimum GPA of 3.0.
• Core and elective courses available.
• Prepares for tech leadership roles.
• Emphasizes practical skills and research.
• Admission requires proficiency in CS areas.
• Tailored education to career goals.
• Cutting-edge technology focus.

San Francisco State University's Master of Science in Data Science and Artificial Intelligence stands out for its focus on Algorithms, AI, and Machine Learning, preparing students for cutting-edge industry roles or further academic research. This campus-based program requires 30-33 units, blending rigorous theoretical foundations with practical applications in big data platforms, statistical learning, and data visualization. Admission prerequisites include a bachelor's degree in a quantitative field, a 3.0 GPA, GRE scores, and proof of English proficiency for international applicants. The curriculum is designed to foster expertise in software development, ethical AI practices, and interdisciplinary collaboration, culminating in a research project or thesis. Unique features include optional industrial research and a strong emphasis on hands-on training and real-world applications.

• 30-33 units program
• Focus on Algorithms, AI & Machine Learning
• Big Data Platforms & Systems
• Probability, Statistics, and Statistical Learning
• Data Visualization and Visual Data Analytics
• Applications and Best Practices
• Supervised Research and Culminating Experience
• Optional Supervised Industrial Research
• Campus-based program
• Prepares for industry and doctoral programs

Dominican University of California offers a Master of Science in Business Analytics (MSBA), a STEM-designated program blending online and on-campus learning. This 12-month hybrid course is tailored for those aiming to master big data, AI, and machine learning without prior experience. It's AACSB accredited, ensuring quality education that prepares students for careers as data analysts or scientists. The program emphasizes practical projects and has a tuition of $1,190 per unit for 36 units. Admission requires a bachelor's degree, resume, statement of purpose, and one recommendation letter, with no GRE needed. International students benefit from a 3-year OPT and access to a robust Bay Area alumni network.

• STEM-designated program
• 12-month duration
• Hybrid format
• No prior experience required
• AACSB accredited
• Covers AI and machine learning
• Practical, hands-on projects
• $1,190 per unit tuition
• 36 units total
• Bachelor's degree required

California State University-East Bay's Master of Science in Computer Science with a concentration in Artificial Intelligence and Machine Learning equips students with cutting-edge skills in AI and machine learning. This program stands out for its practical approach, blending theory with hands-on experience in areas like computer vision and machine learning algorithms. Designed for aspiring tech professionals, it offers late afternoon or evening classes, making it accessible for working individuals. Admission criteria include a bachelor's degree in computer science or a related field, a minimum GPA of 3.0, and completion of prerequisite courses. A capstone project or thesis is required, showcasing the student's mastery of the subject. Notably, the program emphasizes close faculty-student interaction and prepares graduates for lucrative careers in the rapidly evolving tech industry.

• Focus on AI and Machine Learning.
• Small class sizes.
• Flexible scheduling for professionals.
• Requires bachelor's in CS or related.
• 3.0 GPA for admission.
• Capstone project or thesis.
• Late afternoon or evening classes.
• Close faculty-student interaction.
• Prepares for high-demand tech careers.
• Includes computer vision course.

Santa Clara University's M.S. in Electrical and Computer Engineering with a concentration in Signal Processing and Machine Learning is tailored for students aiming to excel in the tech industry. This 46-unit program combines core engineering principles with specialized courses in signal processing and machine learning, such as ELEN 233, to equip students with the skills needed for innovative roles. A minimum GPA of 3.0 is required, and the program welcomes applicants from diverse technical backgrounds, not strictly limited to Electrical or Computer Engineering. Emphasizing practical applications and research, the curriculum fosters problem-solving abilities and technological innovation. Notably, the program does not mandate a thesis, offering a more flexible path to graduation. Admission does not explicitly require an entrance exam, making it accessible to a broader range of students.

• 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

The University of California-San Francisco offers a Master of Science in Artificial Intelligence and Computational Drug Discovery and Development, a unique 1.5-year campus-based program. This innovative curriculum merges artificial intelligence with drug discovery, focusing on computer science, data science, and machine learning applications in the biopharmaceutical sector. Students engage in 38 units of didactic coursework and a capstone project, delving into systems pharmacology, bioinformatics, and pharmacogenomics. The program not only prepares graduates for pivotal roles in academia and the biopharmaceutical industry but also emphasizes the ethical and societal impacts of AI in healthcare. No entrance exam is required, making it accessible to aspiring innovators.

• 1.5-year program duration
• 38 units of didactic courses
• Capstone project required
• Focus on computer science and data science
• Covers systems pharmacology and bioinformatics
• Emphasizes ethical implications of AI
• Prepares for biopharmaceutical industry roles
• Leadership in academia and industry
• Innovative drug discovery approaches
• Interdisciplinary training

Claremont Graduate University offers an MS in Statistics & Machine Learning, a STEM-designated program that blends rigorous statistical theory with practical machine learning applications. Designed for full-time students, the 32-unit curriculum spans two years, featuring in-depth coursework in nonparametric statistics, machine learning algorithms, and big data analytics. This program stands out for its emphasis on research, offering students the chance to engage in hands-on projects and independent studies that may lead to technical publications. Ideal for those aiming for careers in tech or finance, it also provides international students with extended work authorization opportunities post-graduation. No entrance exam is required for admission.

• 32 total required units
• STEM-designated program
• In-person campus modality
• Two-year full-time completion
• International student work authorization
• Core courses in statistics/machine learning
• Optional independent study publication track