MS in AI Degree Requirements

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While pursuing the residential professional MS degree in AI, you must complete a total of 30 credits of graduate-level coursework with the following requirements:

  • Ethics in AI Requirement (1 course = 3 credit hours)
  • Breadth Requirements听 (4 courses = 12 credit hours)
    • Foundations of AI听 (2 courses = 6 credits)
    • AI Core (2 courses = 6 credit hours)
  • Electives听 (3 Courses = 9 credit hours)
  • Interdisciplinary Requirement (2 Courses = 6 credit hours)

Course Details

To complete the degree requirements, students must complete 30 credits of course hours, according to the course requirements listed below. The following rules apply:

  • You must earn a B or better grade in the ethics class and all breadth courses.
  • Your Plan of Study must be approved by your academic advisor.

Ethics in AI Requirement (1 course = 3 credit hours)

  • CSCI 5XXX/INFO 5XXX: Ethics of AI

Breadth Requirements听 (4 courses = 12 credit hours)

Breadth requirements are designed to accommodate students from a wide variety of academic backgrounds while ensuring that all students gain a common core of knowledge.听

Students will complete at least two courses each from 鈥淔oundations of AI鈥 and 鈥淎I Core鈥 breadths.

Foundations of AI Breadth Requirement (choose any two = 6 credit hours)

The foundations of AI breadth requirement focuses on introducing students to the mathematical and algorithmic foundations needed to be successful in the 铿乪ld of AI. This will include the following courses (subject to periodic review by the Department of Computer Science faculty and graduate committee):

  • APPM 5570: Statistical Methods
  • CSCI 5254: Convex Optimization and Its Applications
  • CSCI 5434: Probability for Computer Science
  • CSCI 5444: Introduction to Theory of Computation
  • CSCI 5535: Fundamental Concepts of Programming Language
  • CSCI 5622: Machine Learning
  • CSCI 5654: Linear Programming
  • CSCI 5646: Numerical Linear Algebra
  • CSCI 5822: Probabilistic Models of Human and Machine Learning.
  • CSCI 5854: Theoretical Foundations of Autonomous Systems

AI Core Breadth Requirement (choose any two = 6 credit hours)

The AI core courses emphasize the core principles and applications of arti铿乧ial intelligence and machine learning. Some of these courses may require Foundations of AI courses as prerequisites.

  • CSCI 5135: Computer-Aided Veri铿乧ation
  • CSCI 5302: Advanced Robotics
  • CSCI 5502: Data Mining
  • CSCI 5722: Computer Vision
  • CSCI 5832: Natural Language Processing
  • CSCI 5839: User Centered Design and Development
  • CSCI 5922: Neural Networks and Deep Learning
  • CSCI 7000: Reinforcement Learning
  • INFO 5612: Recommender Systems

Electives听 (3 courses = 9 credit hours)

Students must complete 3 elective courses. These comprise 5000/6000/7000-level AI courses in a variety of AI sub disciplines including natural language processing, machine learning, robotics, computer vision, and cognitive science. Elective courses will be approved and subject to periodic review by the Department of Computer Science faculty and graduate committee. A list of these courses offered across the campus will be maintained and updated by the Department of Computer Science.

Interdisciplinary Requirement (2 courses = 6 credit hours)

Students must complete two non-computer science AI-related courses. A list of these courses offered across the campus will be maintained and updated by the Department of Computer Science. Examples include:

  • Courses in Math & Statistics from the Department of Applied Mathematics
    • APPM 5460: Differential Equations and Dynamical Systems
    • STAT 5530: Mathematical Statistics
  • Courses in Logic offered by the Department of Philosophy
    • PHIL 5460: Modal Logic
    • PHIL 5480: Formal Methods in Philosophy
  • Courses offered by the ATLAS Institute or the Department of Information Science that are not listed as breadth requirements above
    • INFO 5502: Online Communities
    • INFO 5504: Digital Identity
  • Course in the Department of Geography on spatial data analytics/machine learning
    • GEOG 4003/5100: Topics in Geographic Skills: Machine Learning & Spatial Data
  • Courses from the Leeds School of Business on AI in Business Analytics
    • MSBX 5420: Unstructured and Distributed Data Modeling and Analysis
    • MSBX 5500: Security Analytics with Python and Machine Learning

Transfer Credit

Master's students may request a maximum of nine credit hours taken at another University or within CU (either taken as a non-degree student OR taken as a non-CS student) to be transferred. All transfer requests must have departmental approval, please reach out to your graduate advisor for steps on how to request review of credits. You will need your syllabi, unofficial copy of your transcript, and a confirmation that the classes have not been used towards any other degree (Bachelor鈥檚 or higher).听

Students may not transfer from the Coursera to the residential degree, or vice versa. The Department of Computer Science will consider petitions from students currently admitted to various residential MS degrees in the Department of Computer Science to the newly proposed residential MS in AI degree after the degree is launched. The criteria for approving transfers will include the following information to be reviewed by the graduate committee:听

  • academic background

  • grades

  • statements of purpose

  • letters of recommendation

  • work experience.听

Additionally, transfer courses will be evaluated by the graduate committee of the Department of Computer Science in collaboration with the faculty of record teaching the relevant classes.

Plan of Study

Students will be expected to submit a plan of study, in consultation with their departmental advisor, during their second semester of study. Changes to the plan of study must be approved by the advisor.

The MS AI degree is a professional MS degree, which is a course based degree. As such, it does not offer the option to do a MS thesis or independent study research.

The Graduate School requires that to receive a Master's degree a student must maintain a grade point average of at least 3.0 in all courses taken as a graduate student.

Advising

Please check the听staff directory to see who your advisor is. The person in this role serves as their academic advisor throughout a student鈥檚 academic program. Students consult with their advisor to plan their course of study.

Adequate Progress

Any student who does not enroll for any coursework relevant to Computer Science in any one semester (summer semesters excluded) must supply the department with a written statement describing the reasons for such inactivity and the student's current intentions concerning work towards the degree. This statement must be received by the department by the end of the eighth week of the semester in question. Failure to do so will be regarded as evidence of a lack of interest in continuing in the program. Similarly, any student who does not enroll for any Computer Science course work for three consecutive semesters (summer semesters excluded) will be regarded as showing a lack of interest in continuing in the program. In either case, the student may be asked to explain to the department why the student should not be removed from the degree program, with the department making the final decision on the removal.

Grades

The Graduate School requires that to receive a master's degree, a student must maintain a cumulative grade point average of at least 3.0 in all courses taken as a graduate student. No grade lower than a C can be counted towards the master's degree. No grades lower than B can be counted towards the ethics and breadth requirements..

Time Limit

All requirements for the course based MS degree must be completed within four years of the start of course work.

Switching to the Research-Based Computer Science MS degree program

You may switch to the research-based Computer Science MS degree听for genuine academic reasons on a case-by-case basis via petition to the Graduate Committee and upon recommendation from the faculty member willing to supervise/advise the research work. This can happen only ONCE during your academic tenure at CU 麻豆影院. You may not switch during the term you plan to graduate. Your last term officially begins after the census date of the prior term.听

We do NOT offer a research based MS option within the MS-AI degree program. Since the requirements of the two degrees are different, students will have to follow the MS-CS research based degree requirement to the fullest if they decide to switch. No petitions for exemptions will be entertained.

Process you request for the switch:

  • Look for a faculty advisor who is willing to be your research advisor. Students have many opportunities to make connections with the faculty, such as pre-research advising sessions (in Fall), research expos, research talks, attending that faculty's class, etc.
  • Reach out to the faculty and discuss your plans.
  • Faculty advisor emails the research Grad Advisor their letter of support and requests for your switch.
  • Student then fills out the petition form and uploads this form to the online petition when submitting. They must upload the faculty advisor's letter with their petition.听

Academic Standards

Minimum Grades & GPA Requirements

Students must complete a total of 30 credit hours of approved graduate level coursework with a grade of C or better and a cumulative GPA of at least 3.00.

Any student, who fails to maintain a 3.00 grade point average or to make adequate progress toward completing a degree, as assessed by the student鈥檚 academic/research advisor, will be subject to suspension or dismissal from the Graduate School upon consultation with the major department. The final decision on suspension or dismissal will be made by the Dean of the Graduate School. See the听Graduate School Rules for additional information.

Incomplete (I) Grades

An incomplete (I) grade is given only when students, for documented reasons, beyond their control, have been unable to complete course requirements in the semester enrolled. A substantial amount of work must have been satisfactorily completed before approval of such a grade is given. The final grade (earned by completing the course requirements or by retaking the course) does not result in the deletion of the (I) from the transcript. A second entry is posted on the transcript to show the final grade for the course. At the end of one year, (I) grades for courses that are not completed or repeated are regarded as (F) and are shown as such on the student鈥檚 transcript. Courses with grades of (I) are not included in the computation of grade point averages until a final letter grade has been awarded in that course.

Graduation Checklist

The following Graduate School forms must be submitted to the Department of Computer Science for approval.

Important: Check the Graduate School deadlines prior to the start of the semester.

MS AI Course-Based Option

  • Apply to Graduate.听Students must apply through the听 to graduate. This notifies the Graduate School and your department that you intend to graduate. If you do not complete the requirements for graduation, you must log back in and re-apply to graduate for the new graduation date. You must apply to graduate online whether or not you plan to attend the ceremony.
  • Candidacy Application for Advanced Degree

Professional Internship Credit

The Department of Computer Science has the option of completing three credits of professional internship credit (CSCI 6930) and count these towards their degree requirement.听More information on the professional internship credit. These credits count toward the elective requirements.