Curriculum

Our intensive ten-month curriculum will teach you the requisite analytic skills to work with big data sets such as machine learning and artificial intelligence and to solve complex problems from multiple perspectives.  The curriculum provides a “book-end” approach where business context is taught first, followed by intensive analytic methodology coursework, and ending with a final business application capstone project.  Interwoven in each course in the program will be assignments which will require you to analyze data and present it in at least one of the common modalities used in business including verbal communication with presentation software such as PowerPoint or by written communication such as white papers, memos, and reports.

Pre-requisites
  • Probability & Statistics
  • Linear Algebra
  • R and Python Programming
  • Business Foundations
Fall (15 credits)
Competing through Business Analytics
3 Credits | 2 Weeks
Database Management
3 Credits | 13 Weeks
Intermediate Probability and Statistics
3 Credits | 13 weeks
Machine Learning 1
3 Credits | 13 Weeks
Optimization
3 Credits | 13 Weeks
Spring (15 credits)
Big Data
3 Credits | 12 Weeks
Capstone Project
3 Credits | 3 Weeks
Heuristic Algorithms
1.5 Credits | 6 Weeks
Data Visualization
1.5 Credits | 6 Weeks
Machine Learning 2
3 Credits | 12 Weeks
Artificial Intelligence - Neural Networks, Genetic Algorithms
3 Credits | 12 weeks
Business Foundation Course | 3 credits

Competing Through Business Analytics (3 credits)

Analytics Methodology Courses | 24 credits

Optimization (3 credits)
Intermediate Probability & Statistics (3 credits)
Machine Learning 1 (3 credits)
Database Management (3 credits)
Big Data (3 credits)
Heuristic Algorithms (1.5 credits)
Data Visualization (1.5 credits)
Machine Learning 2 (3 credits)
Artificial Intelligence (3 credits)

Capstone Course | 3 credits

Business Analytics Capstone Project (3 credits)

Students complete a comprehensive business analytics project, from start to finish, in this course to which they apply the knowledge and training from the entire program.  Project data, projects goals, and their sponsors are introduced to students during the spring semester, although all of the intense analytics work is confined within a “sprint” period during the last three weeks of the spring semester after all the other course work is complete.  Students will identify the most appropriate techniques for their projects and then apply one methodology effectively. Projects are characterized as requiring the analysis of vast data and solving complex problems. Problems are provided either by business clients or through online competitions, such as those on kaggle.com. They will define and frame a complex problem, develop a systematic approach to solving it using analytics, generate an innovative solution and persuasively convey that solution using data visualization techniques and communication skills.

The MSBA Program is accredited by AACSB and SACSCOC.