Plan of Study
The MSE Online is a part-time, 24-month-long program, consisting of six semesters, one of which is dedicated to term paper writing. The program typically begins in the Fall semester, and consists of synchronous meetings with program faculty, and asynchronous lectures and assignments.
Courses are typically divided into 7-week long "mini" courses that allow students to concurrently learn a wider range of topics, while scaffolding learning to more advanced topics later in the program. For example, the sample Semester 1 has three mini courses, two that run in parallel for the first half of the semester (17-611 and 17-612), and one that runs by itself in the second half of the semester (17-623). The communications classes are 3-units and meet once a week for the entire semester.
A dedicated student can anticipate completing the program in 6 semesters (2 years). The maximum amount of time allowed to complete the program is 7 years.
Sample Course of Study
Semester 1
17-603 Communications for Software Leaders I
17-611 Statistics for Decision Making
17-612 Business & Marketing Strategy
17-623 Quality Assurance
Semester 2
17-604 Communications for Software Leaders II
17-632 Software Project Management
17-635 Software Architecture
17-642 Software Management Theory
Semester 3
17-643 Quality Management
+ 12 Elective Units¹
Semester 4
17-614 Formal Methods
17-626 Requirements for Information Systems²
17-627 Requirements for Embedded Systems²
17-622 Agile Methods
Semester 5
17-636 Applied Distributed Systems
17-646 DevOps
+ 12 Elective Units¹
Semester 6
17-679 Thesis Writing for Software Leaders
- MSE Online students may enroll in electives at Carnegie Mellon that are offered in the remote modality (REO). Please note that not all CMU courses will be available to MSE Online students. Prior to registration, please confirm with your academic advisor to ensure that the elective course is eligible to be taken by MSE Online students. Note, more REO modality classes are added to the university schedule of courses every semester. Independent study can also be a possibility. Please see program FAQs for independent study proposal process.
Examples of elective courses taken by MSE Online students include:
05-692 Interaction Design Overview
10-601 Introduction to Machine Learning
10-703 Deep Reinforcement Learning & Control
11-611 Natural Language Processing
15-319, 15619 Cloud Computing
17-634 Applied Machine Learning
17-644 Applied Deep Learning
17-647 Data Intensive and Scalable Systems
17-659 Applying Generative AI in Quantum Computing and Machine Learning Software Implementations
17-660 Designing and Managing Software Systems Platforms
17-685 Dynamic Network Analysis
17-691 Machine Learning in Practice
17-692 Product Management Essentials for Engineers
17-695 Design Patterns
17-765 Autonomous Self-Adaptive Systems Using Reinforcement Learning
2. Students must enroll in either 17-626 or 17-627, but not both.