MSDSBA requirements

The master of science in data science and business analytics (MSDSBA) curriculum is structured to be completed in a single year (fall, spring/summer, and winter) or a two-year program for part-time students, with a total of 30 credit hours required. The program offers three areas of specialization: advanced analytics, computational engineering, or data-driven business.

Trained by world-class faculty under the stewardship of a strong Industrial Advisory Board, students will learn identification and framing of problems; acquisition, management, and utilization of large and fast-moving streams of data; creation, analysis, solution, and interpretation of mathematical models using appropriate methodology; and the integration of these interdisciplinary skills to enable graduates to successfully develop and execute data science and business analytics projects.

The interdisciplinary core includes nine hours of coursework across business, computer science and industrial engineering. On top of this integrated breadth of study covering the core areas of data science and business analytics, each student has nine hours of track-specialized courses to give them depth in an engineering, business or analytics area of specialization. Each student's six credits of elective choices can be personalized to support their individual career goals.

The final piece of the curriculum is a six-credit applied analytics practicum, in which students will work with companies and organizations on real analytics problems.

Base curriculum: All tracks

  • Data Science Analytics (3 credits)
  • Data Science Strategy & Leadership (3 credits)
  • Computing Platforms for Data Science (3 credits)
  • Choose one of three specialization tracks, each consisting of:
    • Three core courses (9 credits)
    • Two elective courses (6 credits)
  • Practicum (6 credits)

Each student's course choices must satisfy the requirements of at least one of the defined tracks (advanced analyticscomputational engineering or data-driven business).

Track options

Advanced analytics track

The advanced analytics track provides students with a greater knowledge and understanding of the quantitative methodology of descriptive, predictive, and prescriptive analytics: how to select, build, solve and analyze models using methodologies such as parametric and non-parametric statistics, regression, forecasting, data mining, machine learning, optimization, stochastics and simulation. Advanced analytics curriculum

Computational engineering track

The computational engineering track provides students with a deeper understanding of the practice of dealing with so-called Big Data: how to acquire, preprocess, store, manage, analyze, and visualize data arriving at high volume, velocity and variety. Computational engineering curriculum

Data-driven business track

The data-driven business track provides students with a deeper understanding of the practice of using analytics in business and industry: how to understand, frame, and solve problems in marketing, operations, finance, management of information technology, human resources, and accounting to develop and execute analytics projects within businesses. Data-driven business curriculum

Elective courses

The program offers an extensive list of elective courses. Sample list

Capstone experience

At the conclusion of the program, in the spring/summer semester, each student will complete a six-credit applied practicum. Students may pursue an applied analytics internship, working on a significant analytics project at a company or organization site, or they may choose to work in a cross-disciplinary team on a significant data science and business analytics project that companies and organizations bring to campus. Such teams will consist of MSDSBA students from each track to bring each of their specializations to bear in an integrated solution. In this way, the interdisciplinary learning will be emphasized in practice as well as in the classroom.

Additional resources

In addition to learning from world leaders and cutting-edge researchers in data science and business analytics, students in the MSDSBA program will have access to a variety of specialized resources, including:

  • Academic and professional advising
  • Job placement support
  • Funding to attend a major analytics conference
  • Exposure at Wayne State's annual Big Data and Business Analytics Symposium
  • Wayne State's state-of-the-art high-performance computing infrastructure for massive-scale analytics
  • Free cloud computing resources
  • Free and discounted analytics, engineering, and productivity software

How to apply

Admission to the master of science in data science and business analytics program is highly selective. We are looking for exceptional students with a strong interest in data sciences and business analytics, who have shown a high level of ability demonstrated by past performance in appropriate coursework and/or by workplace experience as well as standardized testing.

All applicants are expected to have basic background in mathematics (in particular probability and statistics) and computing (at least one college-level course or equivalent knowledge in computer programming using a high-level language like C, C++, Java, Python, R, FORTRAN, etc.), as well as a bachelor's degree or equivalent. Applicants must submit either GRE or GMAT scores, a professional resume, a personal statement and contact information for three people who will submit letters of recommendation. English Language Proficiency passing test scores (See Graduate School Minimum Test Scores) are required for international applicants.

Applicants who do not have sufficient background in mathematics and computing may still be admitted, with the expectation that they either learn the necessary background material on their own before arriving or take one or more preparatory courses from Wayne State University such as:

  • MAT 5030: Statistical Computing and Data Analysis
  • CSC 3020: Java Programming
  • CSC 2200: Computer Science II

Other courses from online platforms such as Coursera and EdX may be allowed as substitutes on a conditional basis.

Only students with a four-year bachelor's degree in computer science (or a closely related program) are eligible for admission into the Computational Engineering track (listed as "Data Science & engineering" track on the application website) of this program. Exceptions may be made under special circumstances if the applicant can demonstrate equivalent knowledge.

Get started

Click here to begin the application process. You will need to select which program you want to apply for: M.S. in business or M.S. in engineering. Our M.S. programs have three available concentrations: The data-driven business track is in the Mike Ilitch School of Business; the advanced analytics and computational engineering tracks are in the College of Engineering. Make sure that you select the concentration/track when you apply.