Spears School of Business

Plan of study

Students have the choice of specializing in four pre-defined options or creating a customized bundle of electives. Beyond required coursework, on-campus MS BAnDS students are expected to attend specialized trainings and other events to complement the academic curriculum (may occur outside of regular class times).

 

Knowledge prerequisites include some 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 and must be approved by the program director. Students not having any coding background may be required to take a foundational course before starting the program.

 

Core Courses (23 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®, Python, SAS Viya®, 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:  Python, Google TensorFlow via Collab and SAS® Viya

• BAN 5753 Advanced Business Analytics

  A deep dive in applications of Matrix Algebra, Eigen vectors, Principal Component Analysis, LARS & LASSO, Support Vector Machines, Gradient Boosting, Random Forest, Data Engineering and Cloud Computing topics using GCP or Azure. Analytical Tools: GCP or Azure, Power BI, Python and SAS® Viya

• MSIS 5193 Programming for Data Science & Analytics I

  Data analytics lifecycle, Data processing and manipulation, Data visualization, Database connection and data join, String and file manipulation, Regular expressions, Association rule mining, Web scraping, Data extraction using Cloud API, Data analysis using Cloud API and Sentiment analysis. Analytical Tools: Python  

• 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 5663 Advanced Data Wrangling

  Build and query relational databases using SQL. Understand data warehouse technologies and their role within the organization. Implement ETL pipelines using Python. Data wrangling using Python. Work with NoSQL databases using MongoDB. Analytical Tools: SQL Server Express with SQL Server Management Studio, MongoDB, Python.

• *BAN 5560 (1 hour) Research & Communications I

  Critical Thinking, Systems Thinking, Written Communication, Oral Communication, Case Competitions, Year-long Company Projects and Project Management

• *BAN 5570 (2 hours)* Research & Communications II

  Critical Thinking, Creative Thinking, Written Communication, Oral Communication, Case Competitions, Year-long Company Projects, Research paper writing skill and Project Management
  *Pending Regents Approval

• *BAN 5400 (2 hours) Practicum in Business Analytics (Summer Internship)

  * Courses are not required for online students

 

Electives (15 hours)

Students have the choice of specializing in pre-defined options such as marketing analytics, healthcare analytics, advanced data science or cybersecurity analytics.

 

Beyond the four options, students can also work with their advisor to bundle a customized set of electives to prepare them for careers in data engineering, supply chain optimization, advanced statistics and so on.

 

Any of the courses mentioned under any options, careers or other approved electives may be combined to satisfy the 15 hours of the elective requirements for the degree.

• 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

  • BAN 5563 Strategic Marketing and Business Analytics

  • MKTG 5133 Marketing Management

  • ACCT 5183 MBA Financial Reporting

  • Other graduate-level courses as approved by the program director

  Use course catalog to find details about courses

• Advanced Data Science Option (12 hours)

  Required Core (6 hrs):

  • MSIS 5223 Programming for Data Science and Analytics II

  • MSIS 5633 Predictive Analytics Technologies

  Electives (6 hrs):

  • MSIS 5303 Prescriptive Analytics

  • MSIS 5683 Big Data Analytics Technologies

  • MSIS 5713 Scripting Essentials

  • Other graduate-level courses as approved by the program director

  Use course catalog to find details about courses

• Health Analytics (12 hours)

  Required Core (6 hrs):

  • HCA 5013 Survey of Health Care Admin

  • MSIS 5673 Descriptive Analytics and Visualization

  • MSIS 5633 Predictive Analytics Technologies

  Electives (6 hrs):

  • MSIS 5303 Prescriptive Analytics

  • MSIS 5683 Big Data Analytics Technologies

  • Other graduate-level courses as approved by the program director

  Use course catalog to find details about courses

• Cybersecurity Analytics (12 hours)

  Required Core (6 hrs)

  • MSIS 5213 Information Assurance Management

  • MSIS 5713 Scripting Essentials

  Electives (6 hrs)

  • MSIS 5243 Information Technology Forensics

  • MSIS 5713 Scripting Essentials

  • MSIS 5663 Data Warehousing

  • Other graduate-level courses as approved by the program director

  Use course catalog to find details about courses

• Suggested Electives for Data Engineering Careers (12 hours)

  • MSIS 5643 Advanced Database Management Systems

  • MSIS 5663 Data Warehousing

  • MSIS 5683 Big Data Analytics Technologies

  • CS 5123 Cloud Computing

  • CS 5433 Big Data Management

  • CS 5683 Algorithms and Methods for Big Data Analytics

  Use course catalog to find details about courses

• Suggested Electives for Supply Chain Optimization Careers (12 hours)

  • BAN 5551 Optimization Applications in Marketing

  • IEM 5013 Introduction to Optimization (or, MSIS 5303 Prescriptive Analytics)

  • IEM 5063 Network Optimization

  • IEM 5703 Discrete System Simulation

  • IEM 5633 Supply Chain Strategy

  • MSIS 5313 Supply Chain Analytics

  Use course catalog to find details about courses

• Suggested Electives for Advanced Statistics Careers (12 hours)

  • STAT 5213 Bayesian Analysis

  • STAT 5053 Time Series Analysis

  • STAT 5063 Statistical Machine Learning with R

  • STAT 5073 Categorical Data Analysis

  • STAT 5323 Theory of Linear Models

  • STAT 5513 Multivariate Analysis

  Use course catalog to find details about courses

• Other Approved Electives

  • CS 5783 Machine Learning

  • ECON 5113: Managerial Economics

  • EEE 5863: CIE Scholar Practicum

  • FIN 5013: Business Finance

  • MKTG 5243 Base SAS programming for Database Marketing

  • Other graduate-level courses as approved by the program director

     

    Use course catalog to find details about courses

 

In addition to the MS BAnDS degree, students enrolled in this program may also receive SAS® Academic Specializations and accompanying badges (depending on elective courses taken, credentials achieved, etc.). Visit the SAS® Academic Specializations website for more information.