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MEng: Artificial Intelligence (AI) Track

In this age of AI explosion, come learn in the place where "AI" was coined. This track is for engineers who want a rigorous understanding of the foundations of AI: to know where to use AI and use it appropriately, to recognize and anticipate the impacts of AI—both good and bad, and to be an AI architect who can not only see the big picture but also drill down and assess the different paths to the future. Ultimately, the goal is to be able to not just synthesize, but to create new AI solutions for the benefit of society.

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Course Requirements

The program consists of nine courses, of which seven should be from the list of core courses. The remaining two electives can consist of any graduate-level engineering or science courses at Dartmouth.

One of the nine courses must include a term project or product that is sufficient for assessment of the MEng Learning Outcomes. This may be fulfilled by either a core or elective course within the student’s total of nine courses. There are several courses which meet this requirement.

As an on-campus MEng student, you will work with your faculty advisor to develop your program plan to fulfill the MEng requirements, which is approved by the MEng director and submitted to the graduate academic advising director during your first term enrolled in the degree program.

Please note: The information below reflects degree requirements, effective as of fall 2026.

Required Coursework

COURSE TYPE	REQUIRED NUMBER OF COURSES	COURSES
Core Courses	7 courses	Choose seven* courses, from the following:* ENGS 96: Math for Machine Learning ENGS 101: Principles of Reinforcement Learning ENGS 102: Game-theoretic Design, Learning, and Engineering ENGS 105.1: Principles of Causality ENGS 106: Principles of Machine Learning ENGS 108: Applied Machine Learning* ENGS 109: High-dimensional Sensing and Learning (HdSL) ENGG 119: AI in the Real World ENGS 177: Decision-Making under Uncertainty
Electives	2 courses	Choose two* courses, from the following:* Engineering Elective Any graduate-level engineering sciences courses, including the design project elective options. Research Experience Elective For a one-course research experience, students can elect ENGG 192: Independent or Group Study in Engineering Sciences. Design Project Elective Students may take one of the following options to partially fulfill the two-course elective requirement. The appropriate option will depend on each student's prior experience and coursework since the two tracks require different prerequisites. Option 1 (one course) ENGM 191: Product Design and Development Option 2 (two courses) ENGS 190: Engineering Design and Methodology Project Initiation ENGS 290: Engineering Design Methodology and Project Completion Science Elective* Any graduate-level science courses.
Total	9 courses

COURSE TYPE

REQUIRED NUMBER OF COURSES

COURSES

Core Courses

7 courses

Choose seven courses, from the following:

ENGS 96: Math for Machine Learning
ENGS 101: Principles of Reinforcement Learning
ENGS 102: Game-theoretic Design, Learning, and Engineering
ENGS 105.1: Principles of Causality
ENGS 106: Principles of Machine Learning
ENGS 108: Applied Machine Learning*
ENGS 109: High-dimensional Sensing and Learning (HdSL)
ENGG 119: AI in the Real World
ENGS 177: Decision-Making under Uncertainty

Electives

2 courses

Choose two courses, from the following:

Engineering Elective**

Any graduate-level engineering sciences courses, including the design project elective options.

Research Experience Elective
For a one-course research experience, students can elect ENGG 192: Independent or Group Study in Engineering Sciences.

Design Project Elective

Students may take one of the following options to partially fulfill the two-course elective requirement. The appropriate option will depend on each student's prior experience and coursework since the two tracks require different prerequisites.

Option 1 (one course)
ENGM 191: Product Design and Development
Option 2 (two courses)
ENGS 190: Engineering Design and Methodology Project Initiation
ENGS 290: Engineering Design Methodology and Project Completion

Science Elective***
Any graduate-level science courses.

Total

9 courses

* ENGS 108, COSC 274, and QBS 108 have overlapping material, and only one may be taken for credit.

** With the exception of ENGM 191: Product Design and Development, MEng students may not take ENGM courses for credit.

*** Electives from Dartmouth science departments outside of engineering require MEng director approval prior to enrollment. Typically, this approval is granted through the MEng program plan.

Project Course Requirement

One of the nine required courses (core or elective) must be a project course from this section.

ENGS 93: Statistical Methods in Engineering
ENGS 102: Game-theoretic Design, Learning and Engineering
ENGS 103: Operations Research
ENGS 105.1: Principles of Causality
ENGS 107: Bayesian Statistical Modeling and Computation
ENGS 108: Applied Machine Learning
ENGS 118: Electrical Power Systems
ENGS 121: Implementations of Quantum Information
ENGS 139.1: Polar Science & Engineering: Solidification, Sea Ice, Strength & Fracture of Ice

ENGS 142: Intermediate Solid Mechanics
ENGS 146: Computer-Aided Mechanical Engineering Design
ENGS 147: Mechatronics
ENGS 150: Intermediate Fluid Mechanics
ENGS 155: Intermediate Thermodynamics
ENGS 156: Heat, Mass, and Momentum Transfer
ENGS 171: Sustainable Product Design
ENGS 172: Climate Change and Engineering
ENGS 172.2: Techno-economic Analysis in a Developing Country Context

ENGS 175: Energy Systems
ENGS 177: Decision-Making Under Uncertainty
ENGS 190: Engineering Design Methodology and Project Initiation
ENGM 191: Product Design and Development
ENGG 193: Statistical Methods in Engineering
ENGG 199.17: Fundamentals of Additive Manufacturing from Processing to Design
ENGG 230: Fatigue and Fracture
ENGS 290: Engineering Design Methodology and Project Completion