Graduate Degrees in Computer Science and Engineering:
- Master of Science (M.S.) in Computer Science and Engineering
- Master of Science in Engineering (M.S.E.) in Computer Science and Engineering
- Doctor of Philosophy (Ph.D.) in Computer Science and Engineering
- Master of Science (M.S.) in Data Science
Graduate Degrees in Electrical & Computer Engineering:
- Master of Science (M.S.) in Electrical & Computer Engineering
- Master of Science in Engineering (M.S.E.) in Electrical & Computer Engineering
- Master of Engineering (M.Eng.) in Electrical & Computer Engineering
- Doctor of Philosophy (Ph.D.) in Electrical & Computer Engineering
- Graduate Certificate for Computational Discovery and Engineering
- Graduate Certificate for Data Science
- Graduate Certificate for Plasma Science and Engineering
Electrical Engineering and Computer Science (EECS) is one of the highest-ranking EECS departments in the country, and many of the faculty are recognized as leaders in their field. Please review Degree information in both divisions.
Master of Science / Master of Science in Engineering
The M.S. (Master’s of Science) and M.S.E. (Master’s of Science in Engineering) degrees differ mainly in name. The degree requirements are the same. Students with a bachelor’s degree in engineering can elect either degree. Students without an engineering bachelor’s degree are eligible only for the M.S. The principal requirements for the specific M.S. and M.S.E. degrees are listed below. (A more complete statement on master’s degree requirements is available on the Web: http://www.eecs.umich.edu/eecs/graduate/index.html.)
M.S. and M.S.E. in Computer Science and Engineering
A student must satisfy the regulations of the Rackham School of Graduate Studies, the College of Engineering, and the regulations as specified by the program brochure(s) and the program office.
A student must earn at least 30 credit hours of graduate level coursework, of which at least 24 hours must be technical courses, at least 15 hours must be CSE coursework at the 500 level or higher (excluding credit hours earned in individual study, research or seminar courses). The student must also satisfy course requirements in “breadth” areas of software, hardware, artificial intelligence, and theory. A maximum of six credit hours of individual study, research and seminar courses will be accepted toward the master’s degree. The VLSI concentration has slightly different course requirements; please refer to the CSE Brochure for details.
The program requires that the grade point average received in CSE coursework must be at least 3.0 (based on Rackham’s 4.0 scale). An individual course grade of B- or better is required for the credit hours received in any course to be counted towards any master’s degree requirement. A master’s thesis is optional. Credit hours transferred may be applied to meet any master’s degree requirement except the 15 credit hours of 500 level CSE coursework required. (Rackham specifies limitations to the circumstances under which credits may be transferred. See the Rackham Student Handbook.) Courses of an insufficiently advanced level, or which substantially duplicate (in level and/or content) courses already completed by the student, may not be counted as meeting any master’s degree requirements.
M.S. and M.S.E. in Electrical & Computer Engineering
The Master’s Program in Electrical & Computer Engineering covers topics such as Applied Electromagnetics & RF Circuits, Computer Vision, Control Systems, Embedded Systems, Integrated Circuits & VLSI, MEMS & Microsystems, Network, Communication, & Information Systems, Optics & Photonics, Power & Energy, Robotics, Signal and Image Processing & Machine Learning, and Solid State & Nanotechnology. A student must earn at least 30 credit hours of graduate-level coursework, of which at least 24 credit hours must be in technical courses, at least 12 credit hours must be ECE coursework at the 500 level or higher (excluding credit hours earned in individual study, research, or seminar courses, other departments or universities), and 9 credit hours from an ECE major area including at least 6 at the 500 level or above, and at least 6 credit hours in courses outside of ECE. A maximum of 3 credit hours of S/U courses that are not directed study will be accepted toward the degree. At most 6 credit hours of directed study will be accepted. Course grades must be “B-” or better in order to be counted towards any requirements. A grade point average of “B” or higher is required overall. A master’s thesis is optional.
M.Eng. in Electrical & Computer Engineering
The Master of Engineering (M.Eng.) degree in Electrical and Computer Engineering is designed to serve students pursuing a terminal, professional Master’s degree. The degree is offered with a concentration area in either Data Science and Machine Learning (DS/ML), Autonomous systems (AS), or Microelectronics and Integrated Circuits (MI).
The M.Eng. degree, which is distinct from the Master of Science (MS) program and from the M.S. degree in data science, is specially designed for students who plan to enter industry after graduation and who have already decided their specialty. The program is highly structured, emphasizes rigorous theory, practical training, engineering projects, industrial skills, communications, project management, leadership, and entrepreneurial training. The curriculum is aligned with emerging application areas of high workforce demand.
The ECE M.Eng. degree program is a 26-credit program with the following components:
- At least 12 credits in technical courses, of which at least 9 from a set of core courses for a selected M.Eng. concentration; the rest from a set of approved non-core courses.
- At least 4 credits in project and design courses in the same concentration.
- At least 4 and up to 6 credits in ENTR courses; these are in the areas of entrepreneurship, leadership, communication and project management. This requirement may be waived by the M.Eng. program director or the cognizant faculty, in cases such as continuing education and other warranted circumstances.
- An optional summer internship, which can count up to 6 credits, corresponding to a 12-week full-time internship.
Doctor of Philosophy
Ph.D. in Computer Science and Engineering
The doctoral degree is conferred in recognition of marked ability and scholarship in some relatively broad field of knowledge. A part of the work consists of regularly scheduled graduate courses of instruction in the chosen field and in such cognate subjects as may be required by the committee. In addition, the student must pursue independent investigation in a subdivision of the selected field and must present the result of the investigation in the form of a dissertation.
A student becomes an applicant for the doctorate when admitted to the Horace H. Rackham School of Graduate Studies and accepted in a field of specialization. Candidacy is achieved when the student demonstrates competence in their broad field of knowledge through completion of a prescribed set of courses and passing a comprehensive examination.
In most areas, a student must complete required coursework, pass a comprehensive examination and any other program requirements and be recommended for candidacy for the doctorate. A special doctoral committee is appointed for each student to supervise the work of the student both as to the selection of courses and in preparation of the dissertation.
Requirements regarding foreign language and non-technical courses are left to individual departments or programs and to the Graduate School. A prospective doctoral student should consult the program advisor regarding specific details.
Ph.D. in Electrical & Computer Engineering
The Ph.D. Program in Electrical & Computer Engineering covers topics such as Applied Electromagnetics & RF Circuits, Computer Vision, Control Systems, Embedded Systems, Integrated Circuits & VLSI, MEMS & Microsystems, Network, Communication, & Information Systems, Optics & Photonics, Power & Energy, Robotics, Signal and Image Processing & Machine Learning, and Solid State & Nanotechnology.
A student entering the Ph.D. without a relevant Master’s degree, must earn at least 36 credit hours of graduate-level coursework, of which at least 30 credit hours must be in technical courses, at least 12 credit hours must be ECE coursework at the 500 level or higher (excluding credit hours earned in individual study, research, or seminar courses, other departments or universities), and 9 credit hours from an ECE major area including at least 6 at the 500 level or above, and at least 6 credit hours in courses outside of ECE. A maximum of 3 credit hours of S/U courses that are not directed study will be accepted toward the degree. At most 6 credit hours of directed study will be accepted.
A student entering the Ph.D. with a relevant Master’s degree must earn at least 18 credits, including at least 6 technical credit hours, 6 cognate credit hours, and 6 elective credit hours.
Course grades must be “B-” or better in order to be counted towards any requirements. A grade point average of “B” or higher is required overall. In addition, students must complete the following milestones: qualification exam, thesis proposal, dissertation, and dissertation defense. There is an annual progress report in which students must achieve satisfactory progress as determined by the research advisor in order to continue in the program.
Please refer to the ECE Graduate Program manual for details.
Graduate Certificate for Data Science
The University of Michigan Graduate Data Science Certificate Program provides graduate science, technology and skills training for data scientists. The program emphasizes the practice of modeling using modern technology to handle large, incongruent, and heterogeneous collections of data. The Graduate Certificate for Data Science is issued by the Rackham Graduate School. The Program provides interactive data-centered training and involves 9 credits of courses and 3 credits of experiential training that require a written report on data analytics. Michigan Institute for Data Science (MIDAS) faculty from different disciplines provide student mentorship and curriculum advising. MIDAS offers merit-based top-off scholarships for graduate students enrolled in the Certificate program. Completion of the program is expected in 2-4 semesters. The Data Science Certificate program aims to provide core experiences in:
- (Modeling) Understanding of core Data Science principles, assumptions & applications
- (Technology) Data management, computation, information extraction & analytics
- (Practice) Hands-on experience with modeling tools and technology using real data
Who is eligible?
University of Michigan graduate students from any field are eligible to enroll.
There are three fundamental requirements for earning a Graduate Data Science Certificate Program.
- Nine graduate credit hours of coursework in approved courses. These courses are designated as core and elective Methods, Technology or Applications. At most one course may be double-counted with the core graduate degree program (up to 3 credits). It is recommended, but not required, that courses outside the main graduate program of study be selected to broaden the student data-science experiences (e.g., statistics students may take engineering courses, social-science students may take outside statistics and application courses, etc.).
- A Data Science related experience (3 credit semester equivalent, over 160 hours for work). This can take the form of non-credit activity like an internship, practicum, or professional project equivalent to a three credit-hour course, or additional coursework of at least three credits from the approved course list. (This course may be double-counted with another Rackham degree program.) To satisfy this “Plus Requirement” with a data-related experience, students will need to have their supervisor or mentor sign the verification form certifying that the student spent sufficient time working on a data-intense project during that practicum. Alternatively, if allowed and approved by the mentor, students may complete and submit to the DS Certificate Program Chair a report (2-6 pages) describing their experience and results, which will be evaluated to ensure the project demonstrates Data Science content, relevance and applications.
- Regular attendance of the MIDAS Seminar Series, which brings nationally recognized data scientists to U-M, is required. One semester (1-credit) enrollment in EECS 409 (MIDAS Seminar) is required (could count towards the 9 didactic credits). This colloquial training will expose students to current DS developments beyond the boundaries of their own discipline. Students will be required to attend 75% of all seminars (attendance will be taken) to complete the requirement. Viewing archived past MIDAS seminars counts.
Associate Professor Ivo Dinov, https://www.umich.edu/~dinov
The complete Data Science Certificate Program details are available online at https://midas.umich.edu/certificate