CurriculumMSAI (Traditional)
The MSAI (traditional track) program is a full-time, 15-month professional master's degree that explores complex AI technologies and workflows. Students learn to recognize the psychological and design implications of human interactions with intelligent systems and how business needs affect the way intelligent systems are considered and deployed. Supplemented by an internship and projects working with industry partners, graduates will be exceptionally well equipped to create artificial intelligence products with practical impact on the world.
Fall Quarter (First)
Students 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.
Introduction to AI (MSAI 348)
Core techniques and applications of artificial intelligence.
Machine Learning (MSAI 349)
The study of algorithms that improve automatically through experience.
Data Science Seminar (MSAI 339)
Data models and database design.
Frameworks for Artificial Intelligence (MSAI 431)
Framing artificial intelligence to explore the latest challenges in the theory, practice and implications of AI in the modern world. Students take MSAI 431 in Fall and Winter quarters; each quarter is a half course unit.
Elective Course
Students have the opportunity to choose one elective course. Students must take at least one elective in the Fall or in the Winter.
Winter Quarter
Required core courses this quarter include classes in knowledge representation and commonsense reasoning, and collaborative system design.
Knowledge Representation and Reasoning (MSAI 371)
Problem solving, ontologies, reasoning.
Deep Learning (MSAI 437)
A hands-on introduction to deep networks, their varieties, applications, and algorithms used to train them.
Human Computer Interaction (MSAI 330)
Human-Computer Interaction.
Frameworks for Artificial Intelligence (MSAI 431)
Framing artificial intelligence to explore the latest challenges in the theory, practice and implications of AI in the modern world. Students take MSAI 431 in Fall and Winter quarters; each quarter is a half course unit.
Elective Course
Students have the opportunity to choose one elective course. Students who did not take an elective in the Fall must take an elective in the Winter.
Spring Quarter
This quarter students work in teams to complete an industry-led practicum project guided by a corporate partner and overseen by an academic and technical adviser. Students also take a core course in semantic information processing and two electives.
Natural Language Processing (MSAI 337)
Depth of both understanding and generation systems. Focus on representation and inference.
Practicum in Intelligent Systems (MSAI 490)
Students 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.
Two Elective Courses
Students will have an opportunity to choose two 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 either complete an external internship with an industry partner, or work on specific projects or research within an AI lab at Northwestern.
Fall Quarter (Second)
The final quarter allows students the ability to focus on skills to ensure they are ready for the next phase of their professional careers. Students enroll in one core, two electives, and complete a final capstone project.
Law and the Governance of Artificial Intelligence (MSAI 448)
An introduction for engineers to the legal, regulatory, ethical, and policy questions raised by advancements in artificial intelligence and its increasing use.
Industry Capstone Project (MSAI 490)
Students focus on a capstone project that is an extension of either their practicum or independent study project (at Northwestern's AI lab) from the spring quarter or that are based on their work from the summer quarter. The goal is to have all students develop demonstrable systems that become part of their portfolios.
Two Elective Courses
Students have an opportunity to choose two elective courses from a variety of options, including Artificial Intelligence Programming, Design of Problem Solvers, Advanced Computer Vision, or Machine Perception of Music & Audio, among many others.
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.
