Online MS in Information Systems & AI

Program Specific Information for Online MS in Information Systems & AI students can be found at the links below:

Fall 2026 Admits

Fall Semester (7 credits)
BOIS602: AI Augmented Database Management 2 credits
BOIS604: AI Augmented Data Programming in Python3 credits
BOIS631: Statistical Modeling & Data Analytics2 credits
Spring Semester (8 credits)
Digital Transformation Strategy2 credits
Digital Platforms and Ecosystems2 credits
Dynamic Project Management (fully asynchronous)2 credits
Harnessing AI for Business2 credits
Fall Semester (8 credits)
Designing Agentic AI Systems2 credits
Business Process Analysis2 credits
Data Science and Predictive Analytics2 credits
Elective TBD2 credits
Spring Semester (7 credits)
Industry Practicum3 credits
Elective TBD2 credits
Elective TBD2 credits

The Online MS in Information Systems & AI curriculum is 30 credits. The curriculum and course offerings are subject to change.

Students join the Smith School with a variety of technical skills and educational and professional backgrounds. The resources below have been compiled to assist incoming new MS in Information Systems & 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. 

 

Required Software Installation 

MS in Information Systems & AI students must have the following software ready to use on their personal computers before the first day of class:

MS in Information Systems & AI students will also be utilizing the following software:

  • Tableau (access/download at https://www.tableau.com/academic/students; free for academic use when using @umd.edu email address)
  • Python (access/download at https://www.anaconda.com/download)
  • 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 Online Asynchronous Modules 

First semester courses will focus on analytical principles to guide complex decision-making. A strong understanding of basic business math, basis statistics, and spreadsheet skills will be critical to successfully completing the semester. Students who do not already have a strong familiarity with these topics should complete the following before the first day of class:

Required Pre-Semester Online Synchronous Workshops

Two online synchronous workshops are required for incoming MS in Information Systems & 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. 
Students who missed this session may view the recording

Workshop 2: Python for Data Science
Date: Sunday, August 9
Time: 9:00 - 11:00 a.m. 
Students who missed this session may view the recording

Required General Business Skills Modules

The following is required for students without an undergraduate business degree:

 

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.

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

Your Directory ID and password must be set BEFORE you can register; see Directions for Setting Up Directory ID and Password.

Step 1: Log-in to Testudo

Go to: http://www.testudo.umd.edu/
Click on: Registration (Drop/Add)
Enter your Directory ID and Password
Select: Fall 2026

Step 2: Add Three Required Courses

  • Course: BOIS602 
    Section: WI01
    Grade Type: Regular
    Credits: 2
  • Course: BOIS604 
    Section: WI01
    Grade Type: Regular
    Credits: 3
  • Course: BOIS631 
    Section: WI01
    Grade Type: Regular
    Credits: 2

Click Submit. A message may appear stating the course is non-standard; click Enter to bypass this message. All graduate-level courses at the Smith School of Business are non-standard. 

Step 3: Click "View Schedule" to Confirm Courses

  

COURSE SCHEDULE

The Business Master's Academic Calendar varies from the University of Maryland Academic Calendar.

BOIS 604 WI01: AI Augmented Data Programming in Python (3 credits)
Live Session: Tuesdays, 7:00 - 8:00 p.m.
Professor: Manmohan Aseri
Meets: Term A & B (full semester)
BOIS 602 WI01: AI Augmented Database Management (2 credits)
Live Session: Mondays, 7:00 - 8:00 p.m.
Professor: Adam Lee
Meets: Term A		BOIS 631 WI01: Statistical Modeling & Data Analytics (2 credits)
Live Session: Mondays, 7:00 - 8:00 p.m.
Professor: Sujin Kim
Meets: Term B

Courses completed in 7-week sessions are referred to as "terms". Term A meets from August through October, and Term B meets from October through December. For specific dates, review the Academic Calendar.

The schedule is subject to change. Courses may be canceled due to low enrollment without notice.

 

ACADEMIC ADVISING, SCHEDULE CHANGES & COURSE REFUNDS

Students with academic advising questions can contact Feven Girmay. With permission from the academic advisor, students can add, drop, or change course sections during the schedule adjustment period by logging into Testudo. Once the course term has started, students may not receive a full refund when dropping a course. For additional information, please review Penalties for Drops During Schedule Adjustment and Non-Standard Course Dates and Deadlines.

Tuition & Fee information, including due dates and residency information can be found at:

Online MS Tuition & Fees