Master's program curricula
The MS in Data Science and Business Analytics curricula is structured to be completed in a single year (fall, winter, and spring/summer) or a two year program for part-time students, with a total of 30 credit-hours required for each student. The program offers the following majors:
- Advanced analytics (Industrial & Systems Engineering)
- Data-driven business (Technology, Information Systems and Analytics)
- Data computing (Computer Science)
- Statistics (Mathematics)
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 major-specialized courses to give them depth in advanced analytics, data-driven business, data computing or statistics areas of specialization. Each student's six credits of elective choices can be personalized to support their individual career goals.
The final piece of the curricula is a six-credit applied analytics practicum, in which students will work with companies and organizations on real analytics problems.
Base curricula: All majors
- 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 majors (advanced analytics, data computing, data-driven business or statistics).
M.S. Data Science major options:
Advanced Analytics
The Advanced Analytics major 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 methodology such as parametric and non-parametric statistics, regression, forecasting, data mining, machine learning, optimization, stochastics, and simulation.
Data-Driven Business
The Data-Driven Business major 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 in order to develop and execute analytics projects within businesses.
Data Computing
The Data Computing major 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.
Statistics
The Statistics major is designed to meet demand in industry for talent with solid statistical foundations.
Elective courses
The program offers an extensive list of elective courses.
Capstone
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 major 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 M.S. Data Science and Business Analytics 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 Summit
- 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