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MS in Data Science
About the Program
Data science is an interdisciplinary field that uses techniques and theories from mathematics, statistics, computer science, domain knowledge, and information science. It was considered as the fourth (after empirical, theoretical, and computational) paradigm of science by Turing award winner, Jim Gray. A report from McKinsey Global Institute indicates that data scientist is one of the best jobs in U.S. and various industries demand a staggering number of data scientists in the next 10 years.
The Data Science master’s degree program is designed as a 30-credit hour interdisciplinary graduate program. The curriculum consists of required core courses and technical electives, providing opportunities to build knowledge and professional skills in various Data Science areas that are highly demanded in the current job market. Four specializations are recommended (not mandatory) for students with different interests in Data Science: Computational Intelligence Specialization, Applications Specialization, Business Analytics Specialization, and Big Data Informatics Specialization.
This program provides students with opportunities to choose from a variety of courses offered by relevant departments from all four colleges at UM-Dearborn to fulfill students’ specific career objectives in Data Science. These courses have access to a wide variety of computing and other resources across different units at the university.
The department schedules all DS courses during late afternoons or evenings to enable students to earn their master’s degree through part-time study. The program may be completed entirely on campus, entirely online, or through a combination of on-campus and online courses.
If you have additional questions, please contact the program committee chair: Dr. Jie Shen (shen@umich.edu)
Program Details
Learning GoalsEligibility RequirementsPrerequisite Course Descriptions
Curriculum
The 30 semester hours of required coursework are distributed as follows: Core Courses
Core Courses (18 credit hours)
- Required (3 credit hours)
- CIS 556/IMSE 556 Database Systems
- Choose one course (3 credit hours) from:
- CIS 5570 Introduction to Big Data
- IMSE 586 Big Data Analytics and Visualization
- Choose one course (3 credit hours) from:
- ECE 537/CIS 568 Data Mining
- ECE 579 Intelligent Systems
- DS 633 Data Mining for Business Applications
- Choose one course (3 credit hours) from:
- IMSE 514 Multivariate Statistics
- STAT 530 Applied Regression Analysis
- STAT 535 Data Analysis and Modeling
- STAT 560 Time Series Analysis
- Choose one course (3 credit hours) from:
- DS 570 Management Science
- IMSE 500 Models of Operational Research
- Choose one course (3 credit hours) from:
- CIS 545 Data Security and Privacy
- ECE 527 Multimedia Security & Forensics
- HHS 570 Information Science and Ethics
Specializations
Specialization Courses (9 credit hours)
Note that the specializations are offered for guidance only. Students may select three courses from one specialization or three courses from multiple specializations for a broader approach to the degree. For students who are interested in selecting the Business Analytics Specialization, they need to choose 3 courses in that specialization as specified.
One of the following specializations is recommended:
Computational Intelligence Specialization
This specialization is recommended for those students who are interested in building their knowledge and professional skills to solve complex data analytics problems through learning and adapting based on data.
- CIS 511 Natural Language Processing
- CIS 555 Decision Support and Expert Systems
- CIS 5700 Advanced Data Mining
- CIS 579 Artificial Intelligence
- CIS 581 Computational Learning
- CIS 585 Advanced AI
- CIS 685 Research Advances in Artificial Intelligence
- ECE 537/CIS 568 Data Mining
- ECE 552 Fuzzy Systems
- ECE 579 Intelligent Systems
- ECE 5831 Pattern Recognition & Neural Networks
- ECE 679 Advanced Intelligent Systems
- IMSE 505 Optimization
- IMSE 5205 Engineering Risk-Benefit Analysis
- IMSE 559 System Simulation
- IMSE 605 Advanced Optimization
- MATH 520 or ECE 555 Stochastic Processes
- MATH 562 Mathematical Modeling
- MATH 573 Matrix Computations
- STAT 530 Applied Regression Analysis
- STAT 545 Reliability & Survival Analysis
- STAT 560 Times Series Analysis
Applications Specialization
This specialization is recommended for those students who are interested in building their knowledge and professional skills to develop effective data analytics solutions in selected application domains.
- CIS 580 Data Analytics in Software Engineering
- ESCI 585 Spatial Analysis & GIS
- FIN 531 Finance Fundamentals & Value Creation
- HIT 520 Clinical & Evidence-Based Medicine
- IMSE 516 Project Management & Control
- IMSE 561 Total Quality Management & Six Sigma
- IMSE 5655 Supply Chain Management
- IMSE 567 Reliability Analysis
- IMSE 580 Production and Operations Engineering
- MKT 515 Marketing Management
- OM 521 Operations Management
- OM 571 Supply Chain Management
- STAT 545 Reliability & Survival Analysis
- STAT 560 Times Series Analysis
Business Analytics Specialization
This specialization is recommended for those students who are interested in building their knowledge and professional skills to apply intelligent strategies and technologies to support the collection, data analysis, presentation and dissemination of business information in enterprises.
- Choose two courses from:
- DS 630 Applied Forecasting
- DS 631 Decision Analysis
- DS 632 System Simulation
- Choose one course from:
- FIN 531 Financial Fundamentals & Value Creation
- MIS 525 Computer & Information Systems
- MKT 515 Marketing Management
- OM 521 Operations Management
Big Data Informatics Specialization
This specialization is recommended for those students who are interested in building their knowledge and professional skills to apply cutting-edge technologies and tools to tackle Big Data challenges that are essential for data processing and analytics in numerous applications.
- CIS 511 Natural Language Processing
- CIS 515 Computer Graphics
- CIS 534 Semantic Web
- CIS 536 Information Retrieval
- CIS 540 Foundation of Information Security
- CIS 548 Security & Privacy in Cloud Computing
- CIS 552 Information Visualization & Multimedia Gaming
- CIS 554 Information Systems Analysis & Design
- CIS 559 Principles of Social Network Science
- CIS 560 Electronic Commerce
- CIS 562 Web Information Management
- CIS 5570 Introduction to Big Data
- CIS 5700 Advanced Data Mining
- CIS 571 Web Services
- CIS 577/IMSE 577 User Interface Design & Analysis
- CIS 586 Advanced Data Management
- CIS 590J – Selected Topic: Edge Computing
- CIS 652 Advanced Information Visualization and Virtualization
- CIS 658 Research Advances in Data Management
- ECE 524 Interactive Media
- ECE 525 Multimedia Data Storage & Retrieval
- ECE 5251 Multimedia Design Tools I
- ECE 5252 Multimedia Design Tools II
- ECE 528 Cloud Computing
- ECE 576 Information Engineering
- ESCI 585 Spatial Analysis & GIS
- IMSE 570 Enterprise Information Systems
- IMSE 586 Big Data Analytics & Visualization
- OM 665 Information in Supply Chain Management
Capstone Course
Capstone Course (3 credit hours)
In consultation with a faculty advisor, the student should choose between a capstone course (recommended) or one additional course from his/her specialization. Acceptable capstone courses are:
- CIS 695 Master’s Project
- DS 635 Analytics Experience Capstone
- ECE 695 Master’s Project
- EMGT 590 Capstone Project
Note that no more than a total of 15 credit hours may be taken in the College of Business for this degree (core, specializations, and capstone).
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