three students looking at computer

Computer Science MS (Professional Track)
MS

With incredible demand for advanced computing skills across virtually every industry, now is an exciting time to earn a computer science master’s degree, whether you are seeking advancement, higher pay or new opportunities. UWM is one of Wisconsin’s two R1 research universities—an ideal place to bolster your computer science knowledge and skills.

The program welcomes those whose undergraduate degrees were not in computer science.

Our professional track is designed for working professionals in computer science and other fields. This track is available in person, online, and through a combination of the two.

Ranked #11 in Most Affordable Online Computer Programming degrees in 2022 by Intelligent.com

Program Type

Master’s

Program Format

On Campus, Online

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Boost Your Career

A master’s degree in computer science will broaden your knowledge and open the doors to senior positions and career changes. Those holding master’s degree are in high demand and the pay is excellent.

Sample positions, median salaries and projected growth from 2019-2029:*

  • Information security analyst. Salary: $103,590. Growth: 31%
  • Software developers, quality assurance analysts, testers. Salary: $110,140. Growth: 22% Computer and information research scientist. Salary: $126,830. Growth: 15%
  • Computer and information systems manager. Salary: $151,150. Growth: 10%
  • Computer systems analyst. $93,730. Growth: 7%

*U.S. Bureau of Labor Statistics

Satya Nadella and Dean Brett Peters
Microsoft Chairman and CEO Satya Nadella (left) earned his master’s degree from UWM. Shown here with Dean Brett Peters.

What to Expect

This program provides a broad background in critical and emerging aspects of computer science. You can select to concentrate in one of these six areas:

  • Artificial intelligence, machine learning, and natural language processing
  • Database and information systems
  • Image Processing and computer graphics
  • Medical and bio informatics
  • Programming language and compilers
  • Theory and algorithms

Online, in-person, or blended

This track is ideal for working professionals. Each semester, you elect how to complete your studies: online, in-person, or a blend. 

For admission you need only meet UWM Graduate School requirements and have knowledge of computer programming equivalent to our introductory or intermediate undergraduate CS coursework.

You can complete your 31-credit degree in as few as 24 months. No thesis is required.

UWM is known nationally as a leader in online education. The online computer science courses are identical to in-person courses and are taught by the same top-tier faculty.

Tuition:

For fully-online students, the cost for out-of-state students is identical to the rate for in-state students.* The 2023-2024 academic year fee for one 3-credit Computer Science course is $2,799 ($933/credit) and for Computer Studies it is $2,499 ($833/credit). To get this rate, you must sign up for section 210 or 211 of an online course, where the price is shown in the Class Notes. 

*In-state students can get an even lower rate; see this page for details.

Deadlines to Enroll:

  • Fall: March 15
  • Spring: September 15
    • Spring admission is for those students who do not have unmet undergraduate requirements in computing.

Curriculum:

In addition to CompSci courses, the following are non-CompSci pre-approved courses eligible for Professional Track CS MS (as of 5/3/2019).

Up to 9 credits from the following list may be used for your program of study for the Professional Track:

  • All CEAS courses with graduate credit with the exception of COMPST 701 and COMPST 702.
  • All INFOST and MATH courses with graduate credit.
  • The following HCA courses:
    • HCA 541 Healthcare Information Systems Analysis & Design
  • The following HI courses (formerly HCA):
    • HI 700 Introduction to HealthCare Informatics
    • HI 722 Legal, Ethical and Social Issues in Health Care Informatics
    • HI 723 Health Care Systems Applications: Administrative & Clinical
    • HI 740 Introduction to Biomedical Database Applications
    • HI 742 Computational Intelligence in Health Informatics
    • HI 743 Predictive Analytics in Healthcare
    • HI 744 Text Retrieval and Its Applications in Biomedicine
    • HI 745 Health Big Data Processing Platforms
    • HI 760 Biomedical Terminology and Ontology
    • HI 776 Biomedical Natural Language Processing
    • HI 789 Biomedical Information Extraction
  • BUS ADM 544, BUS ADM 546 and any BUS ADM or BUS MGMT course 700 or higher except the following: BUS ADM 701, 740, 741, 743, 810, 813, 817 or any Seminar, Internship, Research Reading, Study Abroad, or Capstone Project/Thesis course.
  • Sociology 928: Seminar in Social Organization: Data & Society

Other courses may be added as requested by students and approved by the faculty.

You may switch to the regular track after completing at least nine credits of 700-level CompSci courses or CompSt751, with at least a 3.5 cumulative GPA. Not all courses acceptable under the professional track may be acceptable under the regular track.

International Students

If you are on a student visa in our masters program, you are normally eligible for “Curricular Practical Training” after two full semesters (Fall and Spring).  You can apply for an internship at a US company (100% time during summer or 50% during a later semester) and concurrently take 1 credit toward your graduate program under the supervision of a professor.

More Information

Contact the College of Engineering & Applied Science Graduate Programs Office or the Computer Science Graduate Program Representative.

Faculty

John Boyland
Boyland, John
  • Professor, Computer Science
Christine Cheng
Cheng, Christine
  • Associate Professor, Computer Science
Mahsa Dabagh
Dabagh, Mahsa
  • Assistant Professor, Biomedical Engineering
  • Affiliate Assistant Professor, Computer Science
Thomas Haigh
Haigh, Thomas
  • Professor, History - General
  • Affiliate Professor, Computer Science
Rohit Kate
Kate, Rohit
  • Associate Professor, Computer Science
Chiu Law
Law, Chiu
  • Associate Professor, Electrical Engineering
  • Associate Professor, Computer Science
Jake Luo
Luo, Jake
  • Associate Professor, Health Informatics & Administration
  • Affiliate Professor, Computer Science
  • Graduate Program Director, Health Care Informatics
Amol Mali
Mali, Amol
  • Associate Professor, Computer Science
faculty photo susan mcroy
McRoy, Susan
  • Professor, Computer Science
  • Department Chair, Computer Science
Ayesha Nipu
Nipu, Ayesha Siddika
  • Teaching Faculty II, Computer Science
Sadia Nowrin
Nowrin, Sadia
  • Teaching Faculty II, Computer Science
Shana Ponelis
Ponelis, Shana
  • Associate Professor, Information Studies Administration
  • Affiliate Professor, Computer Science
Mohammad Rahman
Rahman, Mohammad Habib
  • Richard and Joanne Grigg Professor, Mechanical Engineering
  • Department Chair, Mechanical Engineering
  • Affiliate Professor, Computer Science and Biomedical Engineering
  • Switzer Research Distinguished Fellow
Rock, Jayson
Rock, Jayson
  • Teaching Faculty 3, Computer Science
  • Web Development Certificate Coordinator
Rohit Singh
Singh, Rohit
  • Teaching Faculty II, Computer Science
Bob Sorenson
Sorenson, Robert
  • Teaching Faculty 3, Computer Science
Jerald Thomas
Thomas, Jerald
  • Assistant Professor, Computer Science
faculty image weizhong wang
Wang, Weizhong
  • Associate Professor, Electrical Engineering
  • Associate Professor, Computer Science
faculty member zeyun Yu
Yu, Zeyun
  • Professor, Computer Science
  • Professor, Biomedical Engineering
  • Director, Big Data Analytics and Visualization Lab
Zhen Zeng
Zeng, Zhen
  • Assistant Professor, Computer Science
Jun Zhang
Zhang, Jun
  • Professor, Electrical Engineering
  • Professor, Computer Science
Tian Zhao
Zhao, Tian
  • Associate Professor, Computer Science

Advising

Therese Crary
Crary, Therese
  • Advisor, Graduate Programs
  • Computer Science, Electrical Engineering, Biomedical Health Informatics
Bob Packard
Packard, Robert
  • Advisor, Graduate Programs
  • Civil/Environmental Engineering, Mechanical Engineering, Biomedical Engineering, Industrial/Manufacturing Engineering, Materials Science & Engineering

Guidelines for Professional Work in Lieu of a Capstone

The student should prepare both a written report and an oral presentation. Both components should address the following concerns (as described by the rubric form completed by faculty when assessing Capstone projects).

  • The report and presentation should demonstrate understanding of the broad problem being addressed, as it pertains to the “real world.” It should specify: the target user, the type of task that it supports, the reason the user needs to perform this task, the main limitations to the approach currently used in practice, and what problems those limitations might cause. They should also describe the significance of the work, such as how important this task is to the target business and how large or critical this business is to society or to the economy. If there are other systems that exist that solve the same problem, mention a few of them and why the company chose not to use them if they were available at the time. (If you do not know why it is okay to mention them but indicate that the reasons for pursuing a new solution were not shared with you by the company.)
  • The report and presentation should demonstrate understanding of the solution at a technical level, including links to access any code that was written or, if cloud/commercial software or services were used, the report should include pseudocode for key algorithms. Also, for any tools that were used, the report should assess the relevant capabilities and limitations of each of the tools that you combined in the workflow. An overview, including an architecture diagram, should also be included in the presentation.
  • The report and presentation should include a description of the methods for systematic testing or validation and the findings of the testing, providing quantitative metrics to the extent possible. For qualitative measures, you might survey a sample of the actual users of the system; for example, you could ask:
    • to what extent they feel the solution addressed the target problem,
    • what they consider to be the primary strengths of the solution,
    • what they consider to be the primary limitations of the solution and whether they think it would be worthwhile to address those limitations in the near term.
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Undergraduate Requirements Assessment Form: Professional Track (PDF)

Program of Study Form: Professional Track (PDF)

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Contact Info: ceas-cs@uwm.edu

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