San Francisco State University MS in Data Science and Artificial Intelligence

San Francisco State University offers a Master of Science in Data Science and Artificial Intelligence through its Department of Computer Science. The 30-unit campus program has a direct focus on machine learning, artificial intelligence, statistical learning, big data systems, and applied research.

Quick Facts

SchoolSan Francisco State University
LocationSan Francisco, California
DegreeMS in Data Science and Artificial Intelligence
Credits30 units minimum
FormatCampus
Estimated CA Resident CostAbout $21,068 over 4 full-time semesters, including current mandatory campus fees
Estimated Nonresident CostAbout $35,198 over 4 full-time semesters at 30 units
LengthAbout 2 years full time (planning estimate)
AI / ML FocusStrong: AI, deep learning, data mining, statistical learning, big data, NLP and explainable AI

Curriculum

The official curriculum requires at least 30 units. Students complete coursework across algorithms and AI, big data systems, probability and statistics, data visualization, applications, and supervised research.

Credits and Program Length

The degree requires a minimum of 30 units. SFSU does not publish a fixed completion time on the bulletin page, so about 2 years of full-time study is a reasonable planning estimate for a 30-unit master’s degree. Actual time can vary by course load, prerequisites, and the culminating project or thesis.

Tuition and Cost

For 2026–27, SFSU lists full-time graduate tuition of $4,274 per semester plus $993 in campus fees, for a current total of $5,267 per full-time semester. Based on four full-time semesters, a California resident would pay about $21,068. This is an estimate rather than a university-published total program price.

Nonresidents and international students pay an additional $471 per unit. At 30 units, that adds $14,130, producing an estimated four-semester total of about $35,198. Tuition and fees can change by academic year. See SFSU’s graduate funding and tuition information for current rates and financial aid options.

Admissions

Applicants should have a bachelor’s degree in a quantitative or computing field such as computer science, mathematics, physics, statistics, engineering, or a related area. SFSU expects preparation in programming and quantitative topics, although students with deficiencies may receive conditional admission and complete undergraduate courses during their first year.

Machine Learning, AI, and Data Science Focus

This is a strong fit for MastersInMachineLearning.org because machine learning and AI sit at the center of the degree rather than appearing as optional side topics. The curriculum includes dedicated work in artificial intelligence, deep learning, data mining, statistical learning, generative AI, big data systems, and data visualization. Students can also study natural language technologies and AI explainability and ethics.

Research, Thesis, and Applied Project

Every student completes a culminating experience. Students choose either CSC 895 Applied Research Project or CSC 898 Master’s Thesis. The work includes a software system that uses data to address a significant problem, a written report or thesis, and an oral presentation before a faculty committee.

Who Is This Program Best For?

SFSU’s MS in Data Science and Artificial Intelligence is a good option for students who want a technical, campus-based degree that combines computer science, statistics, machine learning, and applied research. It can also suit applicants from quantitative fields outside computer science who have enough programming and mathematics preparation or are willing to complete prerequisite coursework.

Bottom Line

San Francisco State offers one of the clearest AI and machine learning fits in California: a 30-unit master’s degree with dedicated AI, deep learning, data mining, statistical learning, big data, and research requirements. The estimated California resident cost is about $21,068 over four full-time semesters at current 2026–27 rates, including mandatory campus fees.