Master of Information Systems Management Curriculum
The courses you take in the Master of Information Systems Management program build a foundation for understanding how modern digital infrastructure actually works. Equally important are the decision-making and business-oriented courses. Leadership instruction ensures you can persuade, present and lead teams effectively. Altogether, these skills prepare you to bridge the gap between technical systems and organizational goals.
2027 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)
Fall 2026 current students, please visit the Master of Information Systems Management student handbook.
In Fall 2027, MISM-BIDA 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
- Technology Strategy & Governance
Pathway 2:
Students will take both courses within their selected pathway and may not mix pathways.
The Business Intelligence and Data Analytics pathways share many courses with the core Information Systems Management degree, with some key differences:
- Applied Econometrics (94-834)
- Machine Learning for Problem Solving (95-828)
- Unstructured Data Analytics (95-865)
- 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)
- Statistics for IT Managers (95-796)
- Communicating with Data (95-877)
- Accounting and Finance Analytics (95-719)
- Capstone Project (94-739)
- BIDA Professional Seminar (95-871)
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 (95-876)
- 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.
- Fundamentals of Operationalizing AI (94-879)
- Measuring Social (94-823)
- Data Science and Big Data (95-885)
- Time Series Forecasting in Python (95-835)
- Applications of NL(X) and LLM (94-812)
- Linux and Open Source (95-799)
- Decision Analysis and Multicriteria Decision Making (94-833)
*Elective availability may differ by pathway; 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 can elect one of the following optional concentrations:
- AI Management
- Health Informatics
- Marketing and Social Media Analytics
- Product Management
- Tech Policy and Governance
What can I do with Python?
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 |
Customize Your Degree With a Concentration
Students can elect one of the following optional concentrations:
- AI Management
- Health Informatics
- Marketing and Social Media Analytics
- Product Management
- Tech Policy and Governance
Additional Degree Pathways
