Program specific information for MS in Business Analytics & AI students can be found at the links below:
Fall 2026 cohort
| Fall 2026 Semester (12 credits) | ||
| BUDT 703 | Database Management Systems | 3 credits |
| BUDT 704 | AI Augmented Data Processing and Analysis | 3 credits |
| BUDT 730 | Data, Models, and Decisions | 3 credits |
| BUDT 732 | Decision Analytics | 3 credits |
| Spring 2027 Semester (11 credits) | ||
| BUDT 758D | Data Visualization and Web Analytics | 3 credits |
| BUDT 758J | Enterprise Cloud Computing and Big Data | 3 credits |
| BUDT 758T | Data Mining and Predictive Analytics | 3 credits |
| Elective Options, Choose One: | ||
BUDT 758X BUDT 758Z | Sustainability Analytics Computer Simulation for Business Applications | 2 credits 2 credits |
| Fall 2027 Semester (7 credits) | ||
| BUDT 700 | Business Communication | 1 credit |
| BUDT 758L | Price Optimization and Revenue Management | 3 credits |
| BUDT 770 | Capstone Project in Business Analytics | 3 credits |
The MS in Business Analytics & AI curriculum is 30 credits. Courses are subject to change.
Students join the MS in Business Analytics & AI program with a variety of technical skills and educational and professional backgrounds. The resources below have been compiled to assist incoming new MS in Business Analytics & AI students with preparing for their fall coursework.
All UMD students have unlimited complimentary access to LinkedIn Learning, an online library of >60,000 videos, courses, and career development paths focused on the latest software, creative, and business skills.
View Recording of June 25 MS in Business Analytics & AI Pre-Skills Student Chat
Required Software Installation
MS in Business Analytics students must have the following software ready to use on their personal computers before the first day of class:
- Microsoft Excel (access at https://terpware.umd.edu/Windows/Title/3107)
- Python (access/download at https://www.anaconda.com/download)
- R & R Studio (access/download at https://www.rstudio.com/)
- Tableau (access/download at https://www.tableau.com/academic/students; free for academic use when using @umd.edu email address)
Incoming students do not need to be proficient with these prior to the start of classes, however, having some prior experience will be helpful.
MS in Business Analytics & AI students will also be utilizing the following software in their first fall:
- Lumivero (formerly Palisades) Decision Tools Suite (including AMPL and @Risk; access at http://vsmith.umd.edu; can be downloaded to a Windows-compatible personal computer with code from instructor)
- SQL (access at http://vsmith.umd.edu)
Required Pre-Semester In-Person Workshop for BUDT 730 with Professor Kim
There will be an in-person workshop offered for BUDT 730: Data Models and Decisions with Professor Sujin Kim during New Student Orientation. This workshop will be provided at no cost and will provide an essential foundation for success in this course.
Required Pre-Semester Online Synchronous Workshops
Two online synchronous workshops are required for incoming MS in Business Analytics & AI students who do not have prior experience with Python:
Workshop 1: Getting Started with Python
Date: Sunday, August 2
Time: 9:00 - 11:00 a.m.
Zoom link will be provided by email
Workshop 2: Python for Data Science
Date: Sunday, August 9
Time: 9:00 - 11:00 a.m.
Zoom link will be provided by email
Additional Optional Assignments and Reading
Incoming students do not need to be proficient with all of these tools prior to the start of classes, however, having some prior experience could help them learn more effectively.
- Business Writing and Communications
- Tableau
Access/download at https://www.tableau.com/academic/students; free for academic use when using @umd.edu email address - Power BI
- Python
Access/download at https://www.anaconda.com/download (also available on vSmith at https://go.umd.edu/vsmith-setup)- LinkedIn Learning Course: Python Quick Start
- LinkedIn Learning Course: Python Statistics Essential Training
- LinkedIn Learning Course: Advanced Python
- Books
- Python for Data Analytics: A Business-Oriented Approach (by Daniel H. Groner)
- Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Jupyter, 3rd Edition (by Wes McKinney)
- SQL
Access at http://vsmith.umd.edu - R & R Studio
Access/download at https://www.rstudio.com/
Wednesday, May 27, 2026
Failure to register within one week of receiving instructions may result in the termination of admission to the program. Please review all of the information on this page.
HOW TO REGISTER
Directory ID and password must be set BEFORE registration; see Directions for Setting Up Directory ID and Password.
Step 1: Go to Testudo (Office of the Registrar website)
http://www.testudo.umd.edu/
Click on: Registration (Drop/Add)
Enter Directory ID and Password
Select: Fall 2026
Step 2: Enter Registration Information
Testudo will not allow students to register for courses individually. All MS in Business Analytics students must enter the following information in the "Registration (Drop/Add)" screen of Testudo. Registering this way will enroll students in all Fall 2026 required courses. Testudo will not allow students to register for courses individually.
| Course | Section | Grading Method | Credits |
|---|---|---|---|
MSBD99MB | MB11 | None | Leave blank |
Click "Submit Changes" to complete registration. A message may appear stating the course is non-standard; click "Enter" to bypass this message. Graduate-level courses at the Smith School of Business are non-standard.
Step 3: Confirm Courses
Click "View Schedule" to confirm registration based on the schedule listed below.
COURSE SCHEDULE
For term dates, review the Academic Calendar.
BUDT 704 0506 - AI Augmented Data Processing and Analysis (3 credits) BUDT 732 0506 - Decision Analytics (3 credits) | BUDT 703 0506 - Database Management Systems (3 credits) BUDT 730 0506 - Data Models and Decisions (3 credits) |
Please direct questions to Alex Mainardi.
For general registration information, please see the Registration FAQ.
The schedule is subject to change.
Tuition & Fee information, including due dates and residency information can be found at: