Electrical Engineering and Computer Science (EECS)

Goals

To educate students with a broad and in-depth knowledge of computing systems, and to develop leaders in this field.

Objectives

• Graduates should be able to apply the technical skills necessary to design and implement low-level computer systems and applications.
• Graduates should have the theoretical and practical skills needed for advanced graduate education.
• Graduates should be able to work effectively on teams, communicate in written and oral form, practice life-long learning, and develop the professional responsibility needed for successful technical leadership positions.

Outcomes

The outcome we desire is that our graduates demonstrate:

• An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
• An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
• An ability to communicate effectively with a range of audiences.
• An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts.
• An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives.
• An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
• An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.

Students should also have knowledge of discrete mathematics, probability and statistics, mathematics through differential and integral calculus; sciences; and engineering topics (including computing science) necessary to analyze and design complex electrical and electronic devices, software, and systems containing hardware and software components.

Computer Science

Mission

To provide each student with a solid foundation in the scientific, engineering, and societal aspects of computing that prepares the student for a career that can advance the creation and application of computing technologies for the benefit of society.

Goals

To educate students with core knowledge of the software, hardware, and theory of computing; to give each student in-depth knowledge in one or more computing areas, and to develop leaders in this field.

Objectives

• To provide the necessary foundation in the principles and methods of computer science while preparing students for a broad range of responsible technical positions in industry and/or advanced graduate education.
• To provide the technical skills necessary to design and implement computer systems and applications, to conduct open-ended problem solving, and to apply critical thinking.
• To provide an opportunity to work effectively on teams, to communicate in written and oral form, and to develop an appreciation of ethics and social awareness needed to prepare graduates for successful careers and leadership positions.

Outcomes

The outcome we desire is that our graduates demonstrate:

• An ability to apply knowledge of computing and mathematics appropriate to the program’s student outcomes and to the discipline.
• An ability to analyze a problem, and identify and define the computing requirements appropriate to its solution.
• An ability to design, implement, and evaluate a computer-based system, process, component, or program to meet desired needs.
• An ability to function effectively on teams to accomplish a common goal.
• An understanding of professional, ethical, legal, security, and social issues and responsibilities
• An ability to communicate effectively with a range of audiences.
• An ability to analyze the local and global impact of computing on individuals, organizations, and society.
• Recognition of the need for and an ability to engage in continuing professional development.
• An ability to use current techniques, skills, and tools necessary for computing practice.
• An ability to apply mathematical foundations, algorithmic principles, and computer science theory in the modeling and design of computer-based systems in a way that demonstrates comprehension of the tradeoffs involved in design choices.
• An ability to apply design and development principles in the construction of software systems of varying complexity.

Data Science

Mission

To provide each student with a solid foundation in techniques for deriving insights from data that may be complex, heterogeneous, voluminous, and rapidly changing.

Goals

To produce students with an intellectual understanding of both statistical and computing principles for exploring methods and algorithms related to data science so as to enable knowledge creation and decision-making in various application domains.

Objectives

• To provide the necessary foundation in the principles and methods of data science while preparing students for a broad range of responsible technical positions in industry and/or advanced graduate education.
• To provide the technical skills necessary to ingest, curate, manage, query, analyze, and transform data.
• To provide an opportunity to communicate in written and oral form, to develop an appreciation of ethics, security, and privacy in the digital world, and to prepare graduates for successful careers and leadership positions.

Outcomes

The outcome we desire is that our graduates demonstrate:

• An ability to apply knowledge of mathematics, science, and engineering to problem-solving.
• Knowledge of probability and statistics, including applications appropriate to data science.
• An ability to design and conduct experiments, as well as to analyze and interpret data.
• An ability to select ways of storing and analyzing data to meet desired needs, both in memory and on persistent storage.
• An ability to design and implement automated or semi-automated methods to help curate, query, and transform data.
• An ability to apply machine learning and statistical techniques to help analyze large datasets and to create prediction models or decision models.
• An ability to analyze data in the context of an application domain.
• An understanding of professional and ethical responsibility.
• An ability to communicate effectively.
• The broad education necessary to understand the impact of data science solutions in a global and societal context.

Electrical Engineering

Mission

To provide an outstanding education for engineers in electrical engineering and to develop future leaders.

Goals

To provide students with the education for a rewarding and successful career.

Objectives

• Graduates should be prepared for entry-level engineering jobs, graduate school, or for entrepreneurial activities based on their rigorous education in the fundamentals and applications of electrical engineering, including laboratory and design work.
• Graduates should be able to pursue a variety of careers, based on a curriculum that allows for a balance between a deep education in one area and a broad education in several areas.
• Graduates should be able to work effectively on diverse teams, to communicate in written and oral form, to practice life-long learning, and to develop the professional skills and ethics needed for successful leadership positions.

Outcomes

The outcome that we desire is that our graduates demonstrate:

• An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
• An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
• An ability to communicate effectively with a range of audiences.
• An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts.
• An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives.
• An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
• An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.

Enrollment and Graduation Data

Computer Engineering

The University Registrar publishes the number of students enrolled annually in this program, and the number of degrees granted each term by this program. Additionally you can see recent degrees granted below:

Level	2021	2022	2023
Bachelors Degrees	110	116	104

Computer Science Engineering

The University Registrar publishes the number of students enrolled annually in this program, and the number of degrees granted each term by this program. Additionally you can see recent degrees granted below:

Level	2021	2022	2023
Bachelors Degrees	543	598	609
Masters Degrees	123	113	132
Doctoral Degrees	36	32	37

Data Science Engineering

The University Registrar publishes the number of students enrolled annually in this program, and the number of degrees granted each term by this program.

Level	2021	2022	2023
Bachelors Degrees	0	54	40
Masters Degrees	0	36	40
Doctoral Degrees	0	0	0

Electrical Engineering

The University Registrar publishes the number of students enrolled annually in this program, and the number of degrees granted each term by this program. Additionally you can see recent degrees granted below:

Level	2021	2022	2023
Bachelors Degrees	128	119	96
Masters Degrees	1	1	–
Doctoral Degrees	12	5	–

Electrical and Computer Engineering

Level	2021	2022	2023
Masters Degrees	262	233	459
Doctoral Degree	21	46	55

Accreditation

Electrical Engineering

The Electrical Engineering program is accredited by the Engineering Accreditation Commission of ABET, https://www.abet.org, under the General Criteria and the Program Criteria for Electrical, Computer, Communications, Telecommunication(s) and Similarly Named Engineering Programs.

Computer Engineering

The Computer Engineering program is accredited by the Engineering Accreditation Commission of ABET, https://www.abet.org, under the General Criteria and the Program Criteria for Electrical, Computer, Communications, Telecommunication(s) and Similarly Named Engineering Programs.

Program Outcomes

The matrix maps how each course in our curriculum addresses our program outcomes. Only the outcomes tracked are noted below. 

Course	Student Outcomes (Black – High)
	Apply math and science	Design	Communicate	Ethics	Teams	Experiments, Analyze, and Interpret Data	Lifelong Learning
EECS200
EECS215
EECS300
EECS301
EECS411
EECS413
EECS425
EECS427
EECS430
EECS438
EECS452
EECS470
EECS473
EECS496
TCHNCLCM300
TCHNCLCM496

Undergraduate Degree Program

Requirements

Candidates for the Bachelor of Science in Engineering (Computer Engineering) – B.S.E. (C.E.), the Bachelor of Science in Engineering degree (Computer Science) – B.S.E. (C.S.), the Bachelor of Science in Engineering (Data Science) – B.S.E. (D.S.) and Bachelor of Science in Engineering (Electrical Engineering) – B.S.E. (E.E.) must complete the respective degree requirements. The following Sample Schedules are examples that lead to graduation in eight terms. Candidates for the Bachelor of Science or Bachelor of Arts degree in Computer Science through the College of Literature, Science, and the Arts should consult the LS&A Bulletin for degree requirements.

Students who are admitted to the University of Michigan in Fall 2023 or later must first be selected for the Computer Science major before they can declare. Visit the CSE website to learn more. 

C Rule

A grade of C or higher is required among science, engineering and mathematics courses. Pass/Fail is not permitted for these requirements.

Repeat Policy

Students can attempt each of the three 200-level courses (EECS 203, EECS 280, EECS 281) no more than two times. An attempt includes, but is not limited to, a notation of any letter grade (A-F), withdraw (W), pass/fail (P/F), transfer (T), or incomplete (I) posted on the U-M transcript.

Declaration Requirements

The EECS Department follows the College of Engineering rules for Declaration. For more information see:  “Academic Rules,” then “Declare/Change Major” section of the College Bulletin.

Sample Schedules

B.S.E. in Computer Engineering

The Computer Engineering program is accredited by the Engineering Accreditation Commission of ABET. Please see the PDF version of the sample schedule. Additional information can be found on the CSE Department Advising website.

B.S.E. in Computer Science

The Computer Science program is not an ABET accredited program. Please see the PDF version of the sample schedule. Additional information can be found on the EECS Department Advising website.

B.S.E. in Data Science

The Data Science program is not an ABET accredited program. Please see the PDF version of the sample schedule for students who matriculate to the University of Michigan Fall 2024 or later (F24 sample schedule) or for students who matriculate to the University of Michigan prior to Fall 2024 (Pre-F24 sample schedule). Additional information can be found on the CSE Department Advising website.

B.S.E. in Electrical Engineering

The Electrical Engineering program is accredited by the Engineering Accreditation Commission of ABET. Please see the PDF version of the sample schedule. Additional information can be found on the EECS Department Advising website.

Concentrations

Computer Engineering

The program in Computer Engineering (CE) provides each student with a broad and well-integrated background in the concepts and methodologies that are needed for the analysis, design, and utilization of information processing systems. Although such systems are often popularly called “computers,” they involve a far wider range of disciplines than merely computation, and the Computer Engineering Program is correspondingly broad. A set of required technical courses (along with the college-wide requirements) gives the essential material in circuits, digital logic, discrete mathematics, computer programming, data structures, signals and systems, and other topics. Following completion of this work, the student can select courses in a wide range of subject areas. These include operating systems, programming languages and compilers, computer architecture, microprocessor-based systems, computer aided design and VLSI, digital signal processing, and computer networking, among others. A broad selection from several areas is recommended for most undergraduate students. Specialization in particular areas is more typical of graduate programs of study.

Computer Science

Computer scientists are experts on the theory and practice of computation, including the fundamental capabilities and limitations of computation and how computational thinking can be practically applied. A computer scientist understands how to design and analyze algorithms, how to retrieve, transform, and restore information efficiently, how computers work to execute algorithms, and how to develop software systems that solve complex problems. Specialists within computer science might have expertise in developing software applications, designing computer hardware, protecting computer systems against attacks, developing algorithms, analyzing large data sets, and many other current and emerging possibilities.

The Computer Science (CS) program at the University of Michigan is available to students in both the Colleges of Engineering and of Literature, Science, and the Arts. The program requires students to have a solid foundation in computer software, hardware, and theory, but also gives a student ample opportunity to take advanced electives in areas of computer science such as databases, architecture, networks, artificial intelligence, and graphics, or in emerging interdisciplinary areas such as electronic commerce, web information systems, and computer game design.

Data Science

Huge amounts of data are being collected in all areas, made possible by rapid technological advances over the last few decades. This is further enabling the use of data-driven approaches to fundamentally transform the way corporations do business and is also leading to new discoveries in science and engineering. Data Science affects research and applications in many domains, including education, biological sciences, medical informatics, engineering, healthcare, social sciences, and the humanities. It is a rapidly growing field providing students with exciting career paths, and opportunities for advanced study.

The Data Science major gives students a foundation in aspects of computer science, statistics, and mathematics relevant for analyzing and manipulating voluminous or complex data. Students majoring in Data Science will learn computer programming, statistical analysis and data management, and will learn to think critically about the process of understanding data. Students will also take a capstone experience course that aims to synthesize the skills and knowledge learned in the various disciplines that encompass data science. The Data Science major is a rigorous program that covers the practical use of Data Science methods as well as the theoretical properties underpinning the performance of the methods and algorithms.

The Data Science major is open to students in the Colleges of LSA and Engineering. The Data Science program for the College of Engineering is administered by the CSE Division in the Department of Electrical Engineering and Computer Science. The LSA program is administered by the LSA Department of Statistics.

Electrical Engineering

The Electrical Engineering program provides students with a fundamental background in the basic theoretical concepts and technological principles of modern electrical engineering. A flexible curriculum allows students to emphasize a wide variety of subject areas within the field, including: analog and digital circuits, communication systems, control systems, electromagnetics, integrated circuit (microprocessor) design, signal processing, microelectromechanical devices, solid state electronics, and optics and photonics.

A degree in electrical engineering can lead to a wide range of work opportunities. Automotive applications include engine control processors, sensors to trigger airbags or activate antilock brake systems, development of sophisticated audio systems, and the systems that power electric vehicles. Electrical engineers work in the wireless communications field, including mobile phone systems and global positioning systems. Electrical engineers also work in remote sensing to infer characteristics of a region of the earth from the air or from space to study the environment and climate change. They design, manufacture, test and market the microprocessor, analog and RF integrated circuits from which computers, digital movie and still cameras, the internet, communication systems, and many other modern conveniences are made. Electrical engineers develop signal processing algorithms and hardware for multimedia devices and develop control algorithms and electronics for mechanical systems such as automobiles, robotics, planes and spacecraft. They embed microprocessors in everything from entertainment gadgets to industrial plants. Electrical engineers develop optical fiber communication systems and laser technology for applications ranging from astrophysics to eye surgery. Electrical engineers use semiconductor fabrication technology to make high-efficiency solar cells, light emitting diodes for lighting, and miniature machines called microelectromechanical devices. The signal processing algorithms, optical devices, and miniature systems invented and developed by electrical engineers are providing breakthrough technologies in the biomedical world for health and wellness and the diagnosis and treatment of diseases. A common effort of electrical engineers is to make components smaller, faster, more energy efficient and less costly.

Minors

Computer Science Minor

Electrical Engineering Minor

Sequential Undergraduate/Graduate Study (SUGS)

BSE or BS in one of the EECS programs or Computer Science/MSE or MS in one of the Electrical Engineering and Computer Science (EECS) Programs

There are two separate SUGS programs available through Rackham open to Electrical Engineering and Computer Science undergraduates (depending on major/minor, etc.) who have completed 85 or more credit hours with a cumulative GPA of at least 3.5 (ECE) or at least 3.6 (CSE). Please see the individual program options and contact the respective CSE or ECE Graduate Program Coordinator for more complete program information.

BSE in Electrical Engineering/MS Biomedical Engineering

This SUGS program is open to all undergraduate students from Electrical Engineering who have achieved senior standing (85 credit hours or more) and have an overall cumulative GPA of 3.2 or higher. Please contact the Department of Biomedical Engineering for more complete program information.

Graduate Degrees

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 EECS Departmental website.)

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 Graduate Program Guide 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. A maximum of 6 credit hours of S/U credits will be accepted toward the degree, with up to 3 of those 6 credits being allowed from non-directed study coursework. 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:

1. 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.
2. At least 4 credits in project and design courses in the same concentration.
3. 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.
4. 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 Computer Science and Engineering doctoral degree is primarily intended for students desiring a career in research and/or collegiate teaching.  The focus is on advanced CSE topics, on learning to perform research and to write research papers, and on making fundamental new contributions to a CSE topic. Students take advanced course work and write a doctoral dissertation, also called a thesis.

Students newly admitted to the doctoral program are classified as precandidates. There is a Ph.D. qualifying process, normally completed during the first two years. After all requirements except the dissertation are completed, students become candidates. 

Students entering a CSE doctoral program with a bachelor’s degree typically become candidates in the third year and are strongly encouraged to complete the degree within five years. Such students ordinarily complete the requirements for a master’s degree along the way and receive this degree in addition to the Ph.D. A master’s thesis is optional. Students who enter a CSE doctoral program with a master’s in the field of their program typically become candidates in their second year and are strongly encouraged to complete the degree within four years. Such students are not ordinarily eligible to receive a CSE master’s degree.

Please refer to the CSE Graduate Program Guide for details on degree requirements and program policies.

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, Quantum Engineering Science & Technology, 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 3 credit hours in courses outside of ECE. A maximum of 6 credit hours of S/U courses will be accepted toward the degree. At most 3 of the 6 credit hours of non-directed study coursework 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, 3 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.

Program Requirements

There are three fundamental requirements for earning a Graduate Data Science Certificate Program.

1. 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.).
2. 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.
3.  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.

Program Chair

Associate Professor Ivo Dinov

Please review the Graduate Data Science Certificate Program website for further details.

Graduate Certificate for Plasma Science and Engineering

Michigan Institute for Plasma Science and Engineering (MIPSE) is administering the graduate certificate in Plasma Science and Engineering (PSE). The graduate certificate provides an opportunity for students conducting research in the fundamentals or applications of PSE to both broaden and deepen that experience. The components of the graduate program include:

1. Coursework in the fundamentals and applications of PSE:
   • Plasma courses
   • Supporting courses
   • Download a list of courses (PDF)
2. Participation in the MIPSE Graduate Research Symposium.
3. Research on a topic related to PSE.
4. Opportunity to use internship experiences for laboratory credit.

Information for students interested in pursuing the graduate certificate in PSE

• Overview, Requirements and Admission Procedures
• Application for Admission

Who is eligible?

University of Michigan graduate students from any field are eligible to enroll.

Program Requirements

The requirements for the Graduate Certificate in Plasma Science and Engineering (GPSE) are as follows.

1.  Coursework in the fundamentals and applications of PSE. (Required)

14 Graduate Credit Hours are required for the GPSE. Since the students entering the GPSE are from many different departments and have quite varied backgrounds, specific courses will not be required. Instead, a course of study will be proposed by the student and his/her advisor(s) for discussion and approval by the GPSE Program Committee. The GPSE approved list of courses appears below. Other courses may be approved by request. The recommended breadth requirements are:

·   1 course in plasma fundamentals

·   1 course in plasma technology

·   1 laboratory course

·   1 course in supporting sciences

2. Of the 14 hours required, 1 course (or 3 hours) may be doubled counted from another Rackham graduate degree. This double counting is consistent with Rackham requirements that at most 1/6 of the credits for a graduate degree can be double counted.

3. The laboratory requirement may be satisfied by an appropriate extramural research experience (e.g., internship at a national laboratory, company or collaborating university) that has a substantial laboratory component. Approval must be obtained by petition from the GPSE Program Committee. The extramural experience may satisfy the laboratory requirement but does not count towards the 14 hours required for the certificate unless the student is simultaneously enrolled in an appropriate University of Michigan special topics course.

4. Research on a topic closely related to PSE. (Required) This option may be met in one of two ways:

· Completion of a PhD thesis on a topic closely related to PSE. The appropriate- ness of the thesis topic will be approved by the GPSE Program Committee.

or

· Completion of at least a 1-semester research project on a topic approved by the GPSE Program Committee. The course credits for the research project may count towards the 14 credits required for the certificate.

5. Participation in the GPSE Annual Research Symposium on at least one occasion to report on the results of PSE related thesis research or a PSE related research project. (Required)

The Annual Research Symposium will provide graduate students with an opportunity to present the results of their research in talks and poster sessions, and interact with GPSE faculty and students.

Program Director

Professor Mark Kushner

Please review the Graduate Certificate in Plasma Science and Engineering  website for further details.