The Master of Science in Artificial Intelligence Science allows you to develop both the technical expertise and ethical perspective needed to thrive in a rapidly changing field. You learn to design, implement, and evaluate core AI algorithms with industry-standard tools while mastering data acquisition, preprocessing, and engineering for large and complex datasets. You strengthen your ability to formulate research questions, design experiments, and apply advanced algorithmic techniques to solve real-world problems across diverse domains.

The program welcomes students from all undergraduate disciplines—even if you have no background in AI. If you haven't completed prior coursework in artificial intelligence, you can take preparatory courses after admission to build the necessary foundational skills.

Throughout the program, you critically evaluate the societal, ethical, and environmental implications of AI, engaging with issues of bias, fairness, privacy, and accountability. You practice communicating technical concepts and ethical considerations to both expert and nontechnical audiences, while collaborating in interdisciplinary teams to design and deploy AI solutions responsibly. By cultivating lifelong learning skills and adaptability, you graduate prepared to advance AI in industry and academia.

Requirements for the MS in Artificial Intelligence Science

Completion of all requirements as established by the department graduate committee, the graduate advisory committee, and Graduate Studies, to include

1. Completion of an approved program consisting of 31-33 units of work as follows:
   1. At least 18 of the units required for the degree in 600-level courses.
   2. Completion of the seven core courses.
   3. Completion of one elective course.
   4. Completion of one additional 600-level course related to artificial intelligence if choosing the capstone or project as the culminating activity.
   5. Completion of a culminating activity course.
2. Culminating Activity: Completion and final approval of one of the following three plans as approved by the Graduate Coordinator. (Most students choose the capstone.)
   1. Capstone. This plan includes 28-30 units of coursework and a passing score in the 3-unit capstone course CSCI 693, which is to be taken as part of the last 9 units or during the final semester of the graduate program. The Graduate Coordinator must approve registration in CSCI 693. The research topic area of the capstone culminating activity must involve artificial intelligence. The course may be attempted a maximum of three times; failure on the third attempt will result in dismissal from the program. 
   2. Project. This plan includes 28-30 units of coursework and 3 units of project preparation, CSCI 699P. To qualify for the project path, students must demonstrate exceptional abilities by
      1. Maintaining a GPA of 3.5 or above in their post-baccalaureate coursework.
      2. Being nominated by a faculty member.
      3. Proposing a project related to artificial intelligence.
      4. Having had a project proposal approved by a two-thirds majority vote of the faculty. A formal written description of the project must be submitted to Graduate Studies for approval and accession to the library.
   3. ​Thesis. This plan includes 25-26 units of coursework and 6 units of thesis preparation, CSCI 699T. To qualify for the thesis path, students must demonstrate  exceptional abilities by
      1. ​​Maintaining a GPA of 3.5 or above in their post-baccalaureate coursework.
      2. Being nominated by a faculty member to conduct research.
      3. Having a thesis project related to artificial intelligence.
      4. Having had a thesis proposal approved by a two-thirds majority vote of the faculty. A formal research thesis is required, which must be submitted to Graduate Studies for approval and accession to the library.

3. Approval by the Graduate Coordinator and the Graduate Council on behalf of the faculty of the University.

Course List

Course	Title	Units
CSCI/MATH 417	Applied Linear Algebra for Computer Science	4
CSCI 580	Artificial Intelligence	3
CSCI 581	Machine Learning	3
CSCI 611	Applied Machine Learning	3
CSCI 612	Applied Computer Vision	3
CSCI 650	Algorithms and Computability	3
CSCI 682	Topics in Artificial Intelligence	3
Select one-two of the following: 1		3-8
CSCI 411	Advanced Algorithms
CSCI 551	Numerical Methods and Parallel Programming
CSCI 582	Bioinformatics
CSCI 585	Robotics and Machine Intelligence
CSCI 608	Data Science for Graduate Studies
CSCI 640	Scalable Software Systems
CSCI 644	DevOps Engineering
CSCI 651	Applied Graph Theory
EECE 664	Machine Learning for Engineers
EECE 682	Digital Control System Design Using Artificial Intelligence
Select one of the following:		3-6
CSCI 693	Research Methods in Computer Science
CSCI 699P	Master's Project
CSCI 699T	Master's Thesis 2
Total Units		31-33

¹

Students completing CSCI 699T as their culminating activity select one course. Students completing CSCI 693 or CSCI 699P select an additional course from CSCI 608, CSCI 640, CSCI 644, CSCI 651, EECE 664, or EECE 682.

²

Complete six units of CSCI 699T.

Continuous enrollment is required. At the discretion of the academic program, a maximum of 30 percent of the units counted toward the degree requirements may be special session credit earned in non-matriculated status combined with all transfer coursework. This applies to special session credit earned through Open University, or in courses offered for academic credit through Professional & Continuing Education. Correspondence courses and UC Extension coursework are not acceptable for transfer.

Graduate Time Limit

All requirements for the degree are to be completed within five years of the end of the semester of enrollment in the oldest course applied toward the degree. See Master's Degree Requirements in the University Catalog for complete details on general degree requirements.

Graduate Requirement in Writing Proficiency

All students must demonstrate competency in writing skills as a graduation requirement by successfully completing CSCI 693, CSCI 699P, or CSCI 699T.

Prerequisites for Admission to Conditionally Classified Status

1. Meet all Graduate Studies requirements as specified in Graduate and Postbaccalaureate Admission Requirements.
2. Approval by the department and Graduate Studies.
3. An acceptable baccalaureate from an accredited institution, or an equivalent approved by Graduate Studies.
4. Completion of the Graduate Record Examination (GRE) with a combined score of 300 on the verbal and quantitative portions. Graduates of an ABET accredited computer science program are exempt from this requirement.
5. Submission of a statement of purpose and two letters of reference.

Prerequisites for Admission to Classified Status

In addition to the requirements listed above:

1. Completion of program prerequisites equivalent to CSCI 111, CSCI 211, CSCI 217/MATH 217, CSCI 311, and MATH 315.  Only courses from ABET accredited programs may be used for CSCI 211 and CSCI 311. Students are expected to complete these courses without delay.
2. Courses taken for the purpose of advancement to classified status will not be used towards the MS degree.
3. Meet Graduate Studies requirements.

Advancement to Candidacy

In addition to the requirements listed above:

1. Completion of the Graduate Requirement in Writing Proficiency.
2. Classified graduate standing and completion of, or enrollment in, the graduate core courses.
3. Development of an approved program in consultation with the Graduate Coordinator.
4. Formation of the graduate advisory committee, in the case of the thesis or project plan as described below, in consultation with the Graduate Coordinator.
5. Meet Graduate Studies requirements.

Program Learning Outcomes (PLOs) are clear, measurable statements that describe how students demonstrate mastery of the knowledge, skills, and values of the discipline as appropriate to the degree. Graduates of this program are expected to achieve the following PLOs:

1. Those employed in industry, government, or entrepreneurial endeavors will demonstrate professional advancement through significant technical achievements in artificial intelligence and related fields, expanded leadership responsibility, or other recognition of their contributions.
2. Those who continue their formal education and/or professional growth will pursue advanced degrees, certifications, or industry research and development opportunities in artificial intelligence, computing, science, engineering, business, and other interdisciplinary fields integrating artificial intelligence.
3. All graduates will demonstrate the ability to work effectively as a team member and/or leader in interdisciplinary and ever-changing professional environments shaped by artificial intelligence.