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 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 (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.
Topics Course (MSAI 495)
A half-unit course on an AI-related topic, ranging from leadership to AI platforms.
Winter Quarter
Required core courses this quarter include classes in knowledge representation and commonsense reasoning, and collaborative system design.
Representation, Reasoning, and Language (MSAI 371)
Explores the different ways in which we can represent information, the functionality that each approach enables, and the requirements needed to support them.
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.
Topics Course (MSAI 495)
A half-unit course on an AI-related topic, ranging from leadership to AI platforms.
Spring Quarter
This quarter students work in teams to complete a practicum project. 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)
A design and development experience in which students work to solve an open-ended Artificial Intelligence problem. It provides students with practical experience and helps to emphasize the importance of learning by doing. The project is subject to real-world constraints.
Two Elective Courses
Students will have an opportunity to choose two elective courses from a variety of options, including 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 most students complete an optional external internship.
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 three electives and complete a final capstone project.
Industry Capstone Project (MSAI 490)
The capstone is an opportunity to work on a real-world problem posed by a participating company. Hybrid teams of 4-5 MSAI and MBAi students apply a broad range of business and technical skills over the course of the project. This unique hybrid team approach is designed to mirror the hybrid teams you’ll encounter in your professional lives.
Three Elective Courses
Students have an opportunity to choose three 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.
Highly recommended elective:
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.
