Online MEng: Computer Engineering Academic Overview

The online MEng: CE leverages Coursera's online education platform to deliver the curriculum, allowing you to benefit from interactive video transcription, in-course note taking, and seamless learning across multiple devices—at a schedule and pace that best fits in your life. Online courses include readings, video lectures, assignments, and discussion forums that help spark connections with your peers.

You'll learn to engineer the sensing and computing components of intelligent systems through a series of 9 carefully curated courses, including a capstone. Designed and taught by cross-disciplinary faculty and industry leaders, the curriculum will immerse you in the knowledge and skills necessary to drive the next generation of computer engineering and technology, including virtual/augmented reality, autonomous robots, self-driving cars, AI virtual assistants, wearable/implantable devices, and more.

Through the program, you'll learn to:

• Extract information from data, using a combination of broadly-applicable tools and task-specific techniques such as signal processing, machine learning, and machine vision.
• Implement information-extracting algorithms that fit within the constraints—and utilize the capabilities—of specialized computer hardware for intelligent systems.
• Design, analyze, build, test, and debug sensing and computing components of intelligent systems.
• Collaborate on projects with geographically-diverse team members.

Please note: The information below reflects degree requirements, effective as of Fall 2025.

The online MEng: CE requires a total of nine courses, including a capstone course. Students may take one or two courses at a time (two courses is considered a full-time course load). 

While the order in which most courses are taken is flexible, some courses serve as prerequisites to more advanced courses that require them to be taken early on. For example, ENGG 408: Machine Learning and ENGG 410: Signal Processing are perquisites to ENGG 417: Machine Vision, ENGG 418: Applied Natural Language Processing, and ENGG 419: Deep Learning. 

The capstone course, ENGG 499: Smart Sensors, must be taken in your final term of enrollment and can be taken concurrently. 

Students who completed a BE at Dartmouth may substitute ENGS 110 for ENGG 410: Signal Processing and ENGS 128 for ENGG 463: Advanced FPGA Design, if this double-counting adheres to the general rules governing counting courses towards both the BE and the MEng (i.e. the course did not count towards any AB requirement).

The nine courses fall into the following broad groups:

These sample course plans provide examples of how you might progress through the program either part-time or full-time with a Fall or Spring term start. You do not need to follow these plans exactly—your schedule may be different depending on balancing other responsibilities. Once enrolled, you'll be given a degree path planner to help guide your journey through the program. Program staff are available for any assistance along the way.