Key Program Components
This part-time, online program has three components:
- Asynchronous online learning (self-paced)
- Synchronous live weekly meetings with faculty and peers (all held online, these meetings take place every Tuesday from 7:00-9:45 pm CST)
- Five required in-person immersives
Elective Topics
Students may choose electives based on areas of business:
- Finance
- Supply Chain and Marketing
- General Business Studies
Course Schedule
Summer #1
6 credits
- Core: Data Science Programming (3)
- Core: Information Management (3)
Fall #1
6 credits
- Core: Introduction to Machine Learning (3)
- Core: Financial Management (3)
Spring #1
5 credits
- Core: Advanced Machine Learning (3)
- Core: Analytics for Unstructured Data (2)
Summer #2
6 credits
- Core: Optimization-I (2)
- Core: Unsupervised Learning (2)
- Elective (2)
Fall #2
7 credits
- Core: Optimization-II (2)
- Core: Capstone Preparation (1)
- Elective (2)
- Elective (2)
Spring #2
6 credits
- Core: Capstone Project (2)
- Elective (2)
- Elective (2)
Learning Formats
This course is a blend of self-paced online learning and live online classes.
- All courses are held 100% online.
- Courses can be attended from anywhere in the United States.
- The 5 on-campus “immersives” will be held at The McCombs School of Business in Austin, Texas.
Important Dates: Future Students
For incoming and prospective students: Class of 2027
April 1, 2025: Final application deadline
Immersive 1: Orientation: May 29 – May 31, 2025
Immersive 2: October 2025
Immersive 3: May 2026
Immersive 4: October 2026
Immersive 5: May 2027
First Class Day: June 5, 2025
Graduation: May 2027
Weekly meetings will be held on Wednesdays.
Important Dates: Current Students
This program is robust and impactful. The immersives make it completely unique.
I was looking to be challenged and I knew this was the program to do it.
The Value of MSBA Online
Technical Skill Development
By end of Aug. Year 1
- Exploratory Data Analysis
- Retrieve/manipulate data from centralized (SQL) & Snowflake (Cloud) processing architectures
- Clean, filter, & reorganize data for use in AI/ML algorithms
By end of Dec. Year 1
- Build predictive analytics models using ML
- Extract business meaning from ML model output
By end of May Year 1
- Engineer data sets based on user-generated content from the web
- Build AI-based predictive & descriptive algorithms
Summer, Fall, and Spring Year 2
- Develop advanced AI/ML models for prescriptive analytics
- Study deep learning architectures & apply to GenAI models
Business Skill Development
By end of Aug. Year 1
- Network & collaborate with stakeholders
By end of Dec. Year 1
- Communicate technical solutions effectively to non-technical teams
By end of May Year 1
- Scrape user forums & social networks data & use AI to extract business-actionable information
Summer, Fall, and Spring Year 2
- Apply business analytics tools to evaluate & quantify business tradeoffs
- Manage end-to-end project for sponsoring company in Capstone project
- Explore & specialize in business domains with electives in marketing, supply management, pricing & finance analytics
Equipped for these Business Analytics Roles
*These roles may require more technical experience than what is covered in the MSBA program.
By end of Aug. Year 1
- Data Analyst
- Business Intelligence (BI)
- Developer/Analyst
By end of Dec. Year 1
- Junior Data Scientist
By end of May Year 1
- AI Data Scientist
- AI-Based Business Analyst
Summer, Fall, and Spring Year 2
- AI/ML Project Manager
- AI/ML Engineer*
- AI/ML Data Engineer*
Create Value for Your Organization
Leverage Data to Quantify Business Tradeoffs
Apply Analytics Across Different Business Areas
Impact Decision Making and Make Better Decisions
Gain Career Relevancy for the Long Term
Evaluate Tradeoffs of Emerging Business Models
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