Online MS in Engineering Management
Master of Science
Earn a master's degree that intersects technology, business, and leadership without the traditional tech background.
100%
online
18+
Months
8
Courses
$24k
$3,000 per course
About the program
Through the Master of Science in Engineering Management (MSEM) program from the College of Engineering at Northeastern University you'll learn how to blend the power of technology and business principles to solve complex challenges and drive innovation in tech-focused industries.
Whether you’re an engineer or a professional from a variety of backgrounds, the 100% online MSEM program will equip you with leadership, management, and technical expertise necessary to manage projects and teams and influence organizational strategy. You'll gain knowledge in project management, data analysis, operations, and business strategy.
By the end of the program, you'll have a strong foundation in project execution, resource management, and decision-making in technology-driven environments. With a diverse set of high-demand skills and a unique combination of engineering expertise and business insight, you will be able to pursue roles in industries such as technology, consulting, and manufacturing.
Skills
- Complex Problem Solving 95%
- Engineering Design Application 85%
- Decision-Making Integration 90%
- Project Management 85%
- Trade-Off Analysis 75%
Skip the application—let your performance pave your way
With the MSEM program’s Fast App pathway, you can skip the application process and use your performance on two initial courses to secure your place in the MSEM program.
Complete two performance-based courses from the MSEM program, get a ‘B’ or better, show proof of your bachelor's degree from an eligible institution by the time you complete the two courses, and you’ll join the next cohort in the master’s degree. All credits earned in the MSEM performance-based courses apply directly to the MSEM degree program.
You can also apply to the program using the standard graduate application for direct admission consideration. Learn more about the standard application requirements at the College of Engineering graduate admissions.
College
Current Fast App dates
Term |
Submit Fast App between |
Enroll by |
Start course(s) |
| Fall 2025 | April 16 - August 11 | August 25, 2025 | September 3, 2025 |
Missed an enrollment deadline? Use the enrollment link in your email to enroll in the current term.
Fill out the fast app to begin your MS in Engineering Management degree today.
Resources
Why Performance-Based Admissions Matter: Insights from Northeastern University
In an era where skills and practical knowledge are highly valued, pursuing a graduate education has become a key stepping stone for professionals aiming to advance their careers. However, for adult learners, traditional admissions processes can create unnecessary...
Engineering Management Pathway Courses
Take a look at the fast app performance-based pathway courses. Use the course outlines to start preparing in advance of the courses starting.
IE 6200: Engineering Probability and Statistics
Studies fundamental concepts of probability. Topics include events, sample space, and discrete and continuous random variables; density functions, mass functions, cumulative probability distributions, and moment generating functions; expectation of random variables; common discrete and continuous probability distributions including binomial, Poisson, geometric, uniform, exponential, and normal; multivariate probability distributions, covariance, and independence of random variables; sampling and descriptive statistics; and parameter estimation, confidence intervals, and hypothesis testing. Also introduces analysis of variance. Requires knowledge of multivariate calculus.
View the IE 6200 course outline
OR 6205: Deterministic Operations Research
Introduces the theory, computation, and application of deterministic models to represent industrial operations. Includes linear programming formulation and solution using spreadsheet and algebraic languages software; simplex, big-M, two-phase, revised simplex, and dual simplex algorithms for solving linear programs; introduction to the theory of simplex, fundamental insight, duality, and sensitivity analysis; transportation, assignment, and transshipment problems; shortest path, minimum spanning tree, maximum flow, minimum cost network flow problems and project networks; and discrete-state and continuous-state dynamic programming models and applications. Requires knowledge of linear algebra.
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