Information Systems MSIS
Degree Awarded: MS in Information Systems (MSIS)
Minimum Required Credits: 30.0
Co-op Option: Available for full-time, on-campus master's-level students
Classification of Instructional Programs (CIP) code: 11.0401
Standard Occupational Classification (SOC) code: 11-3021
About the Program
The Master of Science in Information Systems (MSIS) is an industry‑aligned graduate program designed to prepare technology leaders for the AI-driven enterprise and a future of digital innovation. The curriculum blends data, technology, design, and organizational strategy to equip students with the skills needed to build and manage modern information systems in a rapidly evolving digital world.
The program is designed for both career changers and experienced professionals who want deep, practical expertise in how organizations use data, platforms, intelligent systems, and human‑centered technology to innovate and compete. Students graduate ready to translate complex business needs into robust digital solutions and to lead the teams that deliver them.
The MSIS curriculum is organized around three integrated capability pillars that mirror real workforce expectations and modern IS roles:
1. Systems Design & Digital Delivery
Students learn how to analyze business problems, architect solutions, and manage the delivery of digital products and platforms. This pillar emphasizes skills used in roles such as solutions analyst, IT project manager, systems architect, product owner, and digital transformation consultant.
2. Data Engineering, Analytics & Intelligent Systems
Students learn the design of data infrastructure, analytics pipelines, and intelligent systems that support strategic, data‑driven decisions. This pillar develops skills used in roles such as data engineer, analytics architect, ML systems designer, data product developer, or BI engineer.
3. Digital Systems in Organizational Contexts
Students learn how digital systems are analyzed, configured, and governed within organizational, collaborative, and operational contexts. Emphasis is placed on aligning technology capabilities with work processes, decision-making, and responsible use in complex enterprise environments. This pillar builds skills used in roles such as business systems analyst, digital transformation analyst, product or platform analyst, technology consultant, AI systems or operations analyst.
A graduate co-op is available; for more information, visit the Steinbright Career Development Center's website.
Additional Information
For more information about this program, please contact the School of Computer and Information Sciences
Degree Requirements
| Core Courses | ||
| IS 5617 | Cybersecurity Foundations and Risk Management | 3.0 |
| IS 5640 | Digital Transformation and Information Systems | 3.0 |
| IS 6605 | Advanced Data Management and Analytics | 3.0 |
| IS 6620 | Agile Systems Analysis and Design | 3.0 |
| IS 6638 | Agile and AI-Enabled Project Leadership | 3.0 |
| IS 7681 | IS Capstone | 3.0 |
| or IS 7999 | Master's Thesis | |
| Electives | ||
| Select three (3) courses from the following options: | 9.0 | |
Any IS (Information Science) course at the 5000-8999 level | ||
| Innovation Management | ||
| Leading and Executing Change | ||
| Select one (1) IS (Information Science), CS (Computer Science), or SE (Software Engineering) course at the 5000-8999 level | 3.0 | |
| Optional Co-op Experience | ||
| Co-op is an option for this degree for full-time on-campus students. Students choosing this option will be required to complete COOP 5000 as preparation for their co-op experience. | ||
| Total Credits | 30.0 | |
Program Learning Outcomes
- Analyze organizational information needs and design human-centered solutions that meet specified user, performance, and compliance requirements while aligning with strategic objectives.
- Lead and collaborate in multidisciplinary teams to plan, build, and deliver innovative information systems and services using agile, waterfall and hybrid project management best practices.
- Evaluate and select emerging technologies, architectures, and methodologies analyzing trade-offs to address complex organizational challenges.
- Communicate technical and strategic information clearly and persuasively to diverse audiences (technical experts, business stakeholders, decision-makers) using appropriate visualizations and narratives.
- Apply data-driven and AI-enabled approaches grounded in appropriate analytical techniques to support decision-making while implementing data governance, privacy/security controls, and responsible-AI practices across global contexts.