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Oklahoma State University
Analytics and Data Mining Programs

Spears School of Business at Oklahoma State University

Academic Program - M.S. in Business Analytics and Data Science (MSBAnDS)

The MS in Business Analytics and Data Science (MSBAnDS) program offers students practical data analysis experience by applying knowledge acquired in classrooms to real-world business problems. This program exposes participants to hands-on data analysis experience using state-of-the-art enterprise level analytics software from commercial (such as SAS, IBM and Tableau) as well as open source software such as (Python, R and TensorFlow) which provide great advantages in the competitive job market.

The MS in Business Analytics and Data Science candidates may be required to complete knowledge prerequisites to strengthen their analytics skills. Knowledge prerequisites include programming skills (in either C, C#, C++, Java, SQL, Python), basic statistics and probability concepts and basic business knowledge. These prerequisites may be satisfied by prior coursework, industry experience, or a combination of courses and experience. The program director must approve any previous courses, experience, or combination. Students lacking prerequisites may be asked to complete additional courses beyond the minimum basic requirements of credit hours (at least 37 credit hours for on-campus delivery; or 33 credit hours for electronic delivery to working professionals).

Beyond core courses, MSBAnDS students have the choice of specializing in options such as marketing analytics, healthcare analytics, advanced data science or cybersecurity analytics as shown below. Beyond required coursework, MSBAnDS students are also expected to attend and complete several specialized trainings and boot camps as detailed in the plan of study.

Core Courses (22 hours)

  • BAN 5733 Descriptive Business Analytics (A quick overview of applications of Fundamental Statistical Concepts, Linear Regression, Logistic Regression, Experimental Design, ANOVA, Text Analytics, Decision Tree, Neural Network, RFM, k-Means, Time Series and Survival Data Mining. Analytical Tools: Base SAS, SAS EG, JMP, Tableau and Power BI)
  • BAN 5743 Predictive Business Analytics (A deep dive in applications of predictive modeling and machine learning techniques such as Logistic Regression, Decision Trees, Neural Net, Ensemble Models, KNN, Market Basket Analysis, Text Analytics and Sentiment mining. A quick overview of applications of deep learning models such as CNN and RNN. Analytical Tools: R, Python, Google TensorFlow via Collab, SAS Enterprise Miner and SAS Viya)
  • BAN 5753 Advanced Business Analytics (A deep dive in applications of Matrix Algebra, Eigen vectors, Survival Data Mining, Strategic Econometric models, Principal Component Analysis, LARS & LASSO, Support vector Machines, Gradient Boosting, Random Forest, Deep Learning (DNN, CNN, & RNN), Computer Vision (Object Detection). Analytical Tools: R, Python, TensorFlow via AWS, SAS Enterprise Miner and SAS Viya)
  • MSIS 5633 Business Intelligence Tools & Techniques (Data Warehousing, Visual Analytics, Data Mining Process, Methods, and Algorithms, DM with KNIME, Text, Web, and Social Media Mining, Optimization, Simulation and Heuristics, an introduction to Big Data Analytics. Analytical Tools: SAS Viya, KNIME, Orange, RapidMiner, IBM SPSS, R, Rattle, Simio, Weka, JMP, Excel/Solver)
  • MSIS 5503 Statistics for Data Science (Theories, mechanics and applications of Probability and Probability Distributions, Descriptive & Inferential Statistics, Hypothesis Testing, ANOVA, Regression, Time Series Regression, Chi-Square Distribution and Logistic Regression. Analytical Tools: R)
  • MSIS 5600 Programming for Data Science & Analytics (Data Manipulation, Descriptive Analysis, Web Mining Regular Expression, Static and Dynamic web, Social Medial Platforms, Data visualization, Deviation Analysis, multivariate Analysis, Text Mining with Sentiment Analysis. Analytical Tools: R and Python)
  • *BAN 5560 (1 hour) Research & Communications I (Critical Thinking, Creative Thinking, Written Communication, Oral Communication, Case Competitions, Year-long Company Projects, Research paper writing skill and Project Management)
  • *BAN 5560 (1 hour) Research & Communications II ((Critical Thinking, Creative Thinking, Written Communication, Oral Communication, Case Competitions, Year-long Company Projects, Research paper writing skill and Project Management)
  • *BAN 5400 (2 hours) Practicum in Business Analytics (Summer Internship)

* Courses are not required for online students

Electives (15 hours)

Students may specialize in options (below) or, mix-and-match any approved courses to satisfy elective requirements.

Marketing Analytics Option (12 hours)

Required Core (6 hrs):

  • BAN 5763 Advanced Marketing Research Analytics
  • MKTG 5253 Advanced SAS Programming

Electives (6 hrs):

  • BAN 5511 Web Analytics and Digital Marketing
  • BAN 5521 Geographical Information System (GIS) Applications in Marketing
  • BAN 5551 Optimization Applications in Marketing
  • BAN 5561 Customer Lifetime Value Applications in Marketing
  • MKTG 5133 Marketing Management
  • ACCT 5183 MBA Financial Reporting
  • Other courses as approved by program director

Advanced Data Science Option (12 hours)

Required (6 hrs):

  • MSIS 5223 Advanced R/Python
  • MSIS 5663 Data Warehousing

Electives (6 hrs):

  • MSIS 5303 Prescriptive Analytics
  • MSIS 5683 Big Data Analytics Technologies
  • MSIS 5713 Scripting
  • MSIS 5900 Advanced Topics
  • Other courses as approved by program director

Health Analytics

Required Core (6 hrs):

  • HCA 5013 Survey of Health Care Admin
  • MSIS 5673 Descriptive Analytics and Visualization

Electives (6 hrs):

  • MSIS 5303 Prescriptive Analytics
  • MSIS 5663 Data Warehousing
  • MSIS 5683 Big Data Analytics Technologies
  • Other courses as approved by program director

Cybersecurity Analytics (12 hours)

Required Core (6 hrs)

  • MSIS 5213 Information Assurance Management
  • MSIS 5773 Upper Layers of Telecom Systems

Electives (6 hrs)

  • MSIS 5243 Information Technology Forensics
  • MSIS 5713 Scripting Essentials
  • MSIS 5663 Data Warehousing
  • Other courses as approved by program director
Other Approved Electives
  • CS 5783 Machine Learning
  • CS 5433 Big Data Management
  • ECON 5113: Managerial Economics
  • EEE 5863: CIE Scholar Practicum
  • FIN 5013: Business Finance
  • IEM 5013 Introduction to Optimization
  • IEM 5063 Network Optimization
  • MSIS 5303: Prescriptive Analytics
  • MSIS 5643: Advanced Database Management Systems
  • MKTG 5243 Base SAS programming for Database Marketing
  • STAT 5213 Bayesian Analysis
  • STAT 5053 Time Series Analysis
  • STAT 5073 Categorical Data Analysis
  • Other courses as approved by program director

In addition to the MSBAnDS degree, students enrolled in this program may also receive all of the following three certificates (depending on elective courses taken, credentials achieved, etc.):