Master of Engineering in Computer Engineering

A flexible, industry-aligned curriculum designed by Dartmouth engineering faculty

This nine-course curriculum is designed for working professionals and offers flexibility (some courses have prerequisites) in course sequencing while maintaining a clear, structured path through the program. 

The curriculum spans these core areas: Extracting Information from Data, Hardware for Intelligent Systems, and the Capstone preparing students  to design, build, and deploy intelligent systems at scale. Courses in Extracting Information from Data include Machine Learning and Signal Processing, followed by Deep Learning, Applied Natural Language Processing, and Machine Vision. The Hardware for Intelligent Systems area covers Embedded Systems, Advanced FPGA Design, and Distributed Computing.

All courses are designed specifically for this program to reflect today’s engineering challenges and emphasize collaborative, project-based learning. Students work in teams using industry-standard practices, such as two-week sprints and defined deliverables, mirroring real-world engineering environments.