Master’s in Business Data Science and Analytics Curriculum
Building business intelligence in a data-driven world.
The M.S. in Business Data Science and Analytics program focuses on three core areas:
- Training our students to be leaders in data management process and business analytics approaches
- Providing our students with experiential project management opportunities using live data sets for analysis and application
- Developing students’ expertise in key data management areas such as:
- Data mining
- Marketing technology, website analytics and social network analytics
- Applied statistical approaches
- How to interpret and communicate data analysis
The business analytics courses listed are delivered as a full-time, fixed curriculum, cohort-based program. Students will start in January (spring) and graduate the following December (fall).
We register students for all their data and business analytics classes. Please see the academic calendar for specific dates and deadlines on MSU scheduling.
Students must maintain a cumulative grade-point average of 3.0 or higher in all graduate courses. For more information, please refer to the handbook:
Spring Semester
- ITM 818 Data Management and Visualization in Analytics
3 Credits
How digitized business processes and data analytics are essential to the performance and competitive advantage of a modern corporation. Different approaches for strategic data management and business analytics. Real-world cases of successes and failures with analytics-based business strategies.
View full course description at the Office of the Registrar.
- CSE 801a Computational Techniques for Large Scale Data Analysis
3 Credits
Emerging issues in big data (e.g., collection, warehousing, pre-processing and querying; mining, cluster analysis, association analytics; out-of-core, online, sampling-based, and approximate learning algorithms; model evaluation and applications, etc.).
View full course description at the Office of the Registrar.
- ITM 891 Large Scale Data Learning Lab
1 Credit
This course is the lab associated with the CSE 801a course above.
View full course description at the Office of the Registrar.
- ITM 886 Communication Strategies for Analytics
1 Credit
Development of managerial-level business communication skills focusing on oral and written formats. Translation of technical data for communication to non-technical audiences.
View full course description at the Office of the Registrar.
- ITM 883 Business Analytics Problem Solving (Statistics)
2 credits
Application of statistical concepts including random variables, distributions, parameter estimation, hypothesis testing, analysis of variance and time series analysis. Develop modeling understanding of when to use what analytical capability. SPSS and R software introduced.
View full course description at the Office of the Registrar.
- ACC 822 Information Systems Project Management (corporate project)
Introduction to the project management process in an analytics framework using real-world data. One business’ problems presented and solved by the full cohort, broken into smaller student teams. Approximately 10–11 weeks long.
Summer Semester
- STT 805 Applied Statistics Methods
3 Credits
Fundamental concepts in probability and statistics including hypothesis tests, type I and type II errors, statistical significance and power, uncertainty quantification, bootstrapping, Monte Carlo methods, and advanced statistical modeling. Three-week intensive at start of semester.
View full course description at the Office of the Registrar.
- MKT 829 Web Analytics
3 Credits
The collection and analysis of information from the web, including predicting future behavior, search engine optimization, landing page optimization, and mobile marketing and analytics. Online throughout the summer with in-person meetings in early May.
View full course description at the Office of the Registrar.
- ITM 893 Internship or Practicum
3 Credits
Corporate analytics project or internship designed to integrate strategic business understanding with analytical and modeling skills. Manage project engagement with organization. 10–12 weeks, last week of May through late August.
View full course description at the Office of the Registrar.
Fall Semester
- ITM 881 Social Network Analytics
3 Credits
This course explores the application of network analysis in business contexts. Focus is placed on establishing the basic methods and terminology associated with network analysis and text analytics and then progresses into broad-based applications. Applications of these techniques span a broad range of business contexts, including human resource management, CRM systems, supplier networks and online networks.
View full course description at the Office of the Registrar.
- CSE 801B Data Mining
3 Credits
Techniques and algorithms for knowledge discovery in databases, from data pre-processing and transformation to model validation and post-processing.
View full course description at the Office of the Registrar.
- ITM 885 Machine Learning and Optimization in Analytics
3 Credits
Concepts and application in decision making, (stochastic) gradient descent, supervised learning (such as penalized regression, classification, survival analysis), deep neural networks for classification, optimization in Python and R, advanced topics in machine learning (such as generative models, adversarial learning, meta learning).
View full course description at the Office of the Registrar.
- ITM 888 Capstone Business Analytics Corporate Project
1 Credit
Corporate practicum in the development and delivery of predictive data analysis for strategic decision making in organizations. Application of the principles and tools of analytics to real-world problems in research & development, marketing, supply chain, accounting, finance and human resources management. Development and presentation of analytical insights and recommendations.
View full course description at the Office of the Registrar.
