The Master of Science in Artificial Intelligence program curriculum combines technical skills with real-world integration.The Master of Science in Artificial Intelligence program curriculum combines technical skills with real-world integration.


The Master of Science in Artificial Intelligence is a 15-month (5 quarter) program that combines class work, internships coordinated by the program, research opportunities within Northwestern AI labs, and a capstone project. Students will start the program together in the fall quarter and will take most of their class work together as a cohort.

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Purple highlight = Professional Practicum
(takes place during the final quarter of the program)

Yellow highlight = Independent Study and Capstone Project concurrent with main curriculum
(these take place during the spring and final fall quarters of the program)

Fall Quarter (First) 

Students will take a set of required core courses to establish a baseline body of knowledge for all in the cohort. This quarter focuses on a deep introduction to AI, machine learning and interactive AI systems, and on human cognition.

Frameworks for AI

Framing AI in the context of human cognition, human computer interaction, and the goals of intelligent systems.

Introduction to AI (MSAI 348)

A parallel and a somewhat more intensive version of 348 with more software support.

Machine Learning (MSAI 349)

The study of algorithms that improve automatically through experience.

Data Science Seminar (MSAI 339)

Data models and database design.

Winter Quarter

Required core courses this quarter include classes in semantic information processing, knowledge representation and commonsense reasoning, and collaborative system design. In addition, students will choose from elective courses such as perceptual systems, statistical approaches to language understanding, AI for game development, and robotics.

Natural Language Processing (MSAI 337)

Depth of both understanding and generation systems. Focus on representation and inference.

Knowledge Representation and Reasoning (MSAI 371)

Problem solving, ontologies, reasoning.

Deep Learning Foundations from Scratch (MSAI 495)

A hands-on introduction to deep networks, their varieties, applications, and algorithms used to train them.

Human Computer Interaction (MSAI 330)

Human-Computer Interaction.

Spring Quarter

This quarter the cohort will take classes in deep learning, software management for AI, interactive language systems and one elective. 

Independent Study

Each student will work on an independent study project managed by faculty members in their areas of interest.


Practicum in Intelligent Systems (MSAI 490)

An exploration of AI, ML and Cognitive Computing libraries and APIs that are available today.

Agile Software Development (MSAI 394)

The process of software development from the perspective of both rapid prototyping and responsive relationships with clients.

Conversational Interfaces (MSAI 470)

Conversational interfaces, interactive information systems, interactive task management.

One Elective Course

Students will have an opportunity to choose one elective courses from a variety of options, including Introduction to Robotics, Data Management and Information Processing, Designing and Constructing Models with Multi-Agent Languages, Active Learning in Robotics and Seminar in Statistical Language Modeling 

Summer Quarter

During the summer, all students will either complete external internships with industry partners, or work on specific projects within AI labs at Northwestern.

Fall Quarter (Second)

During the final quarter, we focus on making sure that students are ready for the next phase of their professional careers.

Capstone Project

Students will focus on capstone projects that are extensions of either their independent study projects from the spring quarter or that are based on their work from the summer. The goal is to have all students develop demonstrable systems that will become part of their portfolios.

Practicum Class

Students will take a practicum class in the development of systems using existing libraries and publicly available code bases to give them the experience of building on existing work.


Introduction to Cognitive Modeling (COGSCI 207)

An introduction to the modeling of human cognitive behavior and its adaptation to machine intelligence.

Two Elective Courses

Students will have an opportunity to choose two elective courses from a variety of options, including Artificial Intelligence ProgrammingDesign of Problem SolversAdvanced Computer Vision, or Machine Perception of Music & Audio, among many others.

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Speaker Series

Along with classes, the program hosts an ongoing series of speakers from industry to provide students with a view of the business problems of today and how the technologies and techniques they are learning about can be applied.