UC Berkeley Master of Artificial Intelligence and Machine Learning

UC Berkeley’s Master of Artificial Intelligence and Machine Learning (MAIML) is a full-time, in-person professional degree built around machine learning, artificial intelligence, probability, statistics, data science, and responsible AI. The program requires 24 units over two semesters and is designed for students with strong technical preparation who want intensive AI and ML training in one academic year.

Quick Facts

FactDetails
SchoolUniversity of California, Berkeley
LocationBerkeley, California
DegreeMaster of Artificial Intelligence and Machine Learning (MAIML)
Credits24 units
FormatCampus
Estimated tuition and fees$84,004
Length2 semesters / 1 academic year
AI / ML focusVery high

Curriculum

The MAIML curriculum requires 24 units of coursework plus a comprehensive examination. The first semester focuses on core technical foundations, while the second semester combines responsible AI with three electives.

Fall core courses include DATA C200: Principles and Techniques of Data Science, DATA 245: Foundations of Probability and Statistical Inference, and either COMPSCI 289A: Introduction to Machine Learning or STAT 254: Modern Statistical Prediction and Machine Learning. Students also complete communication training and comprehensive-exam preparation.

In spring, all students take the Applied Case Studies and Responsible AI Seminar and choose three electives. Berkeley lists possible electives in artificial intelligence, computer vision, deep neural networks, deep reinforcement learning, natural language processing, data ethics, optimization, theoretical statistics, applied statistics and machine learning, Bayesian statistics, and time series analysis. Elective availability can change by term.

Credits and Program Length

The program requires 24 units and is completed full time over one academic year. Berkeley states that the program begins in August and concludes in May, with fall and spring semesters only.

More information on the official program page.

Tuition and Cost

Berkeley’s MAIML FAQ lists estimated tuition and fees of $84,004. This figure does not represent the full cost of attendance. Students should also budget for housing, books, food, personal expenses, and health insurance.

Berkeley says scholarships are available based on merit and need, and applicants are reviewed for scholarship consideration through the admission process. Because this is a new program beginning in fall 2027, students should confirm the final tuition and fee schedule before enrolling.

Admissions

Berkeley’s admissions criteria call for a bachelor’s degree in computer science, data science, statistics, applied mathematics, or a closely related field, plus a minimum 3.0 GPA and strong quantitative preparation.

Applicants should have prior knowledge of object-oriented programming, data structures and algorithms, linear algebra, statistics, probability, software engineering, and multivariate calculus. Work or research experience is not required. GRE scores are optional, but Berkeley may consider them as evidence of quantitative ability.

The application requires transcripts, a Statement of Purpose, a Personal History Statement, a resume of no more than two pages, and three recommendation letters. At least one recommendation should come from an academic reference. The application fee is $135 for U.S. citizens and permanent residents and $155 for other applicants.

Applications for the first cohort open September 24, 2026. The deadline is January 11, 2027 at 8:59 p.m. PST, and the first cohort begins in fall 2027.

Machine Learning and AI Focus

This is one of the strongest matches for a machine learning degree on the site. The required curriculum directly covers machine learning, probability, statistical inference, data science, and responsible AI, while electives can extend into deep learning, reinforcement learning, natural language processing, computer vision, optimization, and advanced statistics.

Berkeley states that the degree is designed and taught by faculty from Electrical Engineering and Computer Sciences and Statistics. The program targets technical careers such as machine learning engineering and AI research rather than a broad business analytics path.

Campus Format and Silicon Valley Immersion

MAIML is a campus program. Berkeley describes it as full time and in person at the Berkeley campus. It is not an online or hybrid master’s degree.

Between the fall and spring semesters, students participate in a two-day Silicon Valley immersion. Berkeley says the experience includes visits and discussions with technology companies, startups, venture capital firms, alumni, and industry professionals.

Comprehensive Exam and Responsible AI

Students must pass a comprehensive examination to graduate. The curriculum also includes a required Responsible AI seminar that examines issues such as transparency, fairness, equity, privacy, safety, security, and accountability through applied case studies.

Who Is This Program Best For?

This program is best for students with a strong computer science, data science, statistics, mathematics, or related STEM background who want a concentrated technical master’s degree in AI and machine learning. It is especially attractive for students who can study full time on campus and want to finish in one academic year.

It is a weaker fit for students who need a part-time or online format, lack the required mathematics and programming background, or want a lower-cost graduate option.

Bottom Line

UC Berkeley’s MAIML combines a short one-year format with unusually deep technical coverage of machine learning and AI. The 24-unit curriculum, advanced elective options, comprehensive exam, and Silicon Valley immersion make it a strong choice for technically prepared students. The main tradeoffs are the $84,004 estimated tuition and fees, the full-time campus requirement, and the competitive prerequisite profile.