Information Systems Management Master's Degree: Traditional Track
A Degree for Future Leaders
This track is right for you if:
- You want to use technology to drive business impact
- You are interested in both the technical and human sides of digital transformation
- You want the flexibility to pursue careers in product management, consulting, analytics, and technology leadership
Key Program Information
Application Deadlines
Round 1: December 1, 2026
Round 2: January 10, 2027
Round 3: February 1, 2027
Cost of Attendance
Please visit CMU's Student Financial Services website.
Explore the Program
Master of Information Systems Management Curriculum
In Fall 2027, MISM students will be able to engage more deeply with their area of interest by selecting one of two pathways to pursue in addition to their other core coursework:
Pathway 1:
- Data Engineering & Cloud Computing
- Foundations of AI & Machine Learning
Pathway 2:
Students will take both courses within their selected pathway and may not mix pathways.
Other core classes include:
- A/B Testing (95-819)
- Organizational Design and Implementation (94-700)
- Python for Software Development (95-896)
- Economic Analysis (95-710)
- Decision Making Under Uncertainty (95-760)
- Tech Strategy and Governance (95-867)
- Statistics for IT Managers (95-796)
- Accounting and Finance Analytics (95-719)
- Communicating with Data (95-877)
- Information Systems Management Professional Seminar (95-843)
- Capstone Project (94-739)
- Lean Innovation Lab (94-891) can be an option to meet Capstone Project requirement
- Corporate Start-Up Lab (45-996) can be an option to meet Capstone Project requirement
Students will also choose from targeted electives to gain skills and experience in the following areas:
- Artificial Intelligence
- Operationalizing AI (94-879)
- Practical Deep Learning: Models & Applications (95-876)
- Intro to AI (95-891)
- AI Assessment
- Machine Learning for Problem Solving (95-828)
- Optimization and Decision Modeling for Analytics (90-755)
- Optimization and Risk Modeling for Managers (91-819)
- Technology, Society, and Policy
- Responsible AI Governance (95-841)
- AI, Data, and Society (95-802)
For class, syllabi, and faculty information, please visit the Heinz College course catalog. Fall 2026 students, please visit the Master of Information Systems Management student handbook.
- Measuring Social (94-823)
- Linux & Open Source (95-799)
- Cloud Security (95-746)
- Advanced AI & Business Strategy (94-829)
- Financial Investing (94-818)
- Fundamentals of Operationalizing AI (94-879)
*Elective availability may differ by pathway/location; students may also enroll in graduate-level courses from other Heinz College programs as well as other departments across Carnegie Mellon University’s campus, with approval.
For class, syllabi, and faculty information, please visit the Heinz College course catalog.
Students in the Information Systems Management: Traditional pathway can elect an optional concentration in one of the following specialty areas:
- AI Management
- Health Informatics
- Marketing and Social Media Analytics
- Product Management
- Tech Policy and Governance
Begin Your Path to Innovation
Sample Information Systems Management Class Schedule
- At Carnegie Mellon University, courses are counted in units instead of credits.
- Three units are roughly equivalent to one credit at many of our peer institutions.
- A semester-long course is 12 units, while a half-semester class (called a mini) is six units.
The following schedules are intended to be examples of the structure of the semester. Courses may not always be offered in this fashion.
Fall Semester, Mini 1
| Course Title |
Pathway 1: Data Engineering & Cloud Computing Or Pathway 2: Database Management |
| Python for Software Development |
| Statistics for IT Managers |
| Technology, Society, and Policy Elective: Tech, Society, and Policy |
| Economic Analysis |
Fall Semester, Mini 2
| Course Title |
Pathway 1: Data Engineering & Cloud Computing Or Pathway 2: Database Management |
| Python for Software Development |
| A/B Testing |
| Elective |
Spring Semester, Mini 1
| Course Title |
Pathway 1: Foundations of Applied AI & Machine Learning Or Pathway 2: Distributed Systems for Information Systems Management |
| Communicating with Data |
| Tech Strategy & Governance |
| Decision Making Under Uncertainty |
| Elective |
Spring Semester, Mini 2
| Course Title |
Pathway 1: Foundations of Applied AI & Machine Learning Or Pathway 2: Distributed Systems for Information Systems Management |
| Communicating with Data |
| Tech Strategy & Governance |
| AI Elective: Measuring AI & ML |
