Additional Major


The additional major in artificial intelligence is designed for undergraduates in another major who also want a deep dive into artificial intelligence and machine learning. It provides students with the opportunity to study the technologies and learn how to apply them to their own primary field of interest. The additional major is open to all CMU students, although the required technical courses and pre-requisites may prove challenging for students who lack the necessary background. Students who find the additional major difficult to fit into their schedules might consider the artificial intelligence minor

What You'll Learn

When you earn an additional major in AI, you’ll:

  • Understand how to distill a real-world challenge into an artificial intelligence problem.
  • Design, analyze, implement and use state-of-the-art AI and machine learning techniques for dealing with real-world data.
  • Master the core concepts of computer science, with emphasis on data structures, programming, computing systems, and algorithm design, performance, and correctness across a variety of metrics.
  • Master the fundamentals of discrete mathematics, logic, theorem-proving and explanation, probability and statistics, and optimization.
  • Describe, specify and develop large-scale, open-ended artificial intelligence systems subject to constraints such as performance, available data and need for transparency.
  • Communicate technical material effectively to technical and non-technical audiences.
  • Work productively both individually and in teams.
  • Recognize the social impact of artificial intelligence and the underlying responsibility to consider the ethical, privacy, moral and legal implications of artificial intelligence.


The additional major in artificial intelligence has almost the same requirements as the primary major. The curriculum is as follows:

Prerequisite (1 course)

  • ​Fundamentals of Programming: 15-112 (12 units)

Math and Statistics Core (6 courses)

  • Calculus II: 21-120 (10 units)
  • Concepts of Mathematics: 21‐127, 21‐128 or 15‐151 (minimum 10 units)
  • Integration and Approximation: 21-122 (10 units)
  • Matrices and Linear Transformations: 21-241 (10 units)
  • Probability and Statistics: 36-225 or 21-325 or 36-235, and 36-226 or 36-236, 15-259 and 15-260, or 36-218 (SCS students) (minimum 9 units)
  • Modern Regression: 36-401 (9 units)

Computer Science Core (5 courses)

  • Principles of Imperative Computation: 15-122 (10 units)
  • Principles of Functional Programming: 15-150 (10 units)
  • Parallel and Sequential Data Structures and Algorithms: 15-210 (12 units)
  • Introduction to Computer Systems: 15-213 (12 units)
  • Great Theoretical Ideas in Computer Science: 15-251 (12 units)

Artificial Intelligence Core (2 courses)

  • Introduction to AI Representation and Problem Solving: 15-281 (12 units)
  • Introduction to Machine Learning: 10-315 (12 units)

AI Cluster Electives (4 courses)

Students are required to take one approved course from each of the following four cluster areas.

Cognition and Action Cluster

  • 15-386: Neural Computation
  • 15-482: Autonomous Agents
  • 15-494: Cognitive Robotics
  • 16-350: Planning Techniques for Robotics
  • 16-362: Mobile Robot Programming Laboratory
  • 16-384: Robot Kinematics and Dynamics

Machine Learning Cluster

  • 10-403: Deep Reinforcement Learning and Control
  • 10-405: Machine Learning With Large Datasets
  • 10-414: Deep Learning Systems
  • 10-417: Intermediate Deep Learning
  • 10-418: Machine Learning for Structured Data
  • 10-422: Foundations of Learning, Game Theory and Their Connections
  • 10-423: Generative AI
  • 10-425: Introduction to Convex Optimization
  • 11-441: Machine Learning for Text Mining
  • 11-485: Introduction to Deep Learning
  • 36-402: Advanced Data Analysis

Perception and Language Cluster

  • 11-411: Introduction to Natural Language Processing
  • 11-442: Search Engines
  • 11-492: Speech Processing
  • 15-387: Computational Perception
  • 15-463: Computational Photography
  • 16-385: Computer Vision

Human-AI Interaction Cluster

  • 05-317: Design of Artificial Intelligence Products
  • 05-318: Human-AI Interaction
  • 05-391: Designing Human-Centered Software
  • 16-467: Human-Robot Interaction

Ethics and Human Cognition

The additional major also requires a course in ethics and a course in cognitive psychology or cognitive science. Ethics is an essential component of an AI education, due to the roles AI systems will play in society. Human cognition is an important aspect to study, as much of AI is modeled after human intelligence.

Ethics (1 course)

  • 16-161: Artificial Intelligence and Humanity
  • 16-735: Ethics and Robotics
  • 17-200: Ethics and Policy Issues in Computing
  • 80-249: AI, Society and Humanity

Human Cognition (1 course)

  • 85-211: Cognitive Psychology
  • 85-213: Human Information Processing and Artificial Intelligence
  • 85-370: Perception
  • 85-345: Meaning in Mind and Brain
  • 85-408: Visual Cognition
  • 85-435: Biologically Intelligent Exploration

Note that Concepts in Artificial Intelligence (07-180) is not required for additional majors, although students interested in the additional major in AI are encouraged to take 07-180 prior to taking 15-281 or 10-315, in order to get a general overview of the field.

Double Counting

Students pursuing an additional major in AI can double count at most five courses total from the AI course requirements toward all other majors and minors they’re pursuing. The mathematics, ethics and human cognition courses may double count without restriction, except for 36-402 (Advanced Methods for Data Analysis), which is part of the Machine Learning cluster. Students with majors that overlap substantially with AI should consult with the program coordinator to review their audit for any potential issues.

To Apply

Apply for an Additional Major or Minor
Complete our application including a statement (maximum one page) of why you want to take the additional major and how it fits into your career goals.

Students must have all prerequisites completed, 15-122, 15-150, and one of 15-210, 15-213 or 15-251, as well as 15-281 or 10-315. (10-301 taken prior to fall 2022 will be accepted.) Maintaining a "B" average in aforementioned courses is required for admittance to the additional major. 

Students must apply for admission no later than the semester before they intend to graduate. An admission decision will usually be made within one month. Students are encouraged to apply as early as possible in their undergraduate careers so the advisor of the AI additional major can provide advice on their curriculum. Applications can be accepted based on midterm grades.