MS in Artificial Intelligence

Artificial Intelligence (AI) is an area of study that explores how to create computer programs that learn to make decisions, reason about data, and communicate with humans. In the MS in AI degree program, students learn to apply creative thinking, algorithmic design, and coding skills to build modern AI systems. Students will gain deep technical training and expertise in our focus areas of machine learning, computer vision, and natural language processing.

The program prepares students to work as Artificial Intelligence Engineers in information technology companies or pursue a PhD in computer science.

The 8-course (32-credit) MS in AI program is geared toward students with a computer science undergraduate degree, but we also welcome those with equivalent training and experience, as well as students with gaps in their computing background but strong academic records overall.

Learning Outcomes

Students who complete the MS in AI program will be able to demonstrate:

  • The possession of excellent skills in coding in a high-level, general-purpose programming language (e.g., C++ or Python).
  • The ability to apply coding skills, design skills, and creative thinking to build cutting-edge AI systems.
  • The ability to convert descriptions of abstract AI challenges into descriptions of specific AI project requirements.
  • The knowledge of machine learning, natural language processing, and computer vision design mechanisms, algorithms, and state-of-the-art system architectures.
  • The ability to identify well-defined performance metrics (e.g., sensitivity and specificity of the AI system).
  • The ability to design and run simulations/experiments to validate and enhance system/software performance.
  • The ability to design and develop software as scalable software architectures, components, and APIs (API stands for application programming interface).
  • The ability to work in teams of software engineers.
  • Optional outcome: The ability to write and publicly defend an MS thesis in AI, which includes formulating an AI problem definition, conducting a literature review, developing one or several AI methods, testing the method(s), and discussing the results.
  • Optional outcome: The ability to conduct independent work on a topic in AI, deepening the above-mentioned skill, and to write a report that describes the work in detail.

Course Requirements

1. Core courses:

  • CAS CS 505 Introduction to Natural Language Processing
  • CAS CS 542 Machine Learning
  • CAS CS 585 Image and Video Computing
  • GRS CS 640 Artificial Intelligence

2. At least one course from List A:

  • CAS CS 504 Data Mechanics
  • CAS CS 506 Computational Tools for Data Science
  • CAS CS 562 Advanced Database Applications
  • CAS CS 565 Algorithmic Data Mining
  • CAS CS 660 Graduate Introduction to Database Systems

3. Additional electives from Lists A, B, or C, selected in consultation with the student’s advisor.

List B includes all CAS 500+ and GRS courses in computer science. List C includes AI-related courses offered by another department with the permission of the Director of Graduate Studies.

Students who have already taken courses equivalent to any of the required core courses can substitute other appropriate electives, with the approval of their advisor and the Director of Graduate Studies.

Language Requirement

There is no foreign language requirement for this degree.