AI Curriculum: Master the Future of Artificial Intelligence
Artificial Intelligence Programs
Carnegie Mellon's renowned artificial intelligence program, ranked 2025’s #1 artificial intelligence program in the world, is known for its groundbreaking research and innovative technologies. Students in the program go far beyond fundamentals, reaching into the bleeding edge of technological possibilities to prepare for a more AI-centric future.
The School of Computer Science offers the world’s leading undergraduate bachelor of science in Artificial Intelligence, graduate-level Master of Science in Artificial Intelligence and Innovation, and graduate certificates in Generative AI. Additionally, undergraduate students enrolled at CMU can pursue artificial intelligence as a minor.
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Machine Learning Programs
Since 2006, Carnegie Mellon’s Machine Learning Department has offered comprehensive academic programs, including Ph.D., Master's, and undergraduate options such as a Minor and Concentration in machine learning.
These programs emphasize interdisciplinary research and applications in areas like natural language processing, robotics, and data science. Graduates are prepared to address the growing demand for machine learning expertise across industries.
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Artificial Intelligence Engineering Graduate Programs
Carnegie Mellon's Master of Science in Artificial Intelligence Engineering (MS AIE) integrates AI and machine learning with engineering disciplines, enabling students to develop AI-based solutions for complex engineering challenges.
The program offers core courses in AI systems, machine learning, and trustworthy AI, while allowing specialization within various engineering departments. Graduates are equipped for roles such as data scientists, neuroengineers, and deep learning research engineers.
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AI curriculum and courses across campus
School of Computer Science courses include:
- Computational Photography
- Convex Optimization
- Design of Artificial Intelligence Products
- Human-AI Interaction
- Human Information Processing and Artificial Intelligence
- Machine Learning for Text and Graph-based Mining
- Neural Networks for NLP
College of Engineering courses include:
- Energy Systems Modeling
- Introduction to Deep Learning
- Machine Learning & AI for Engineers
- Special Topics: Systems and Tool Chains for AI Engineers
- Special Topics: Trustworthy AI
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Heinz College of Information Systems and Public Policy courses include:
- Agent-Based Modeling and Digital Twins
- Applications of NL(X) and LLM
- Demystifying AI
- Technologies Transforming Arts Enterprises
- Fundamentals of Operationalizing AI: Mastering AI Lifecycle from Theory to Practice
- Machine Learning for Problem Solving
- Responsible AI: Principles, Policies, Practices
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Mellon College of Science courses include:
- Computational Modeling, Statistical Analysis and Machine Learning in Science
- Future Lab - DNA Science in the Cloud
- Large-Scale Computing in Data Science
- Neural Networks & Deep Learning in Science
- Welcome to the Future Lab - Science in the Cloud
Dietrich College of Humanities and Social Sciences courses include:
- Advanced Methods for Data Analysis
- Machine Learning for Structured Data
- Machine Learning with Graphs
- Machine Learning with Large Datasets
- Modern Regression
- Principles of Iterative Computation
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Tepper School of Business courses include:
- AI Applications in Business
- Applied Business AI
- Design of Artificial Intelligence Products
- Ethics and AI
- Machine Learning for Business Applications
- Optimization for Prescriptive Analytics
- Technology and the Future of Work
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College of Fine Arts courses include:
- Advanced Interaction & Service Design Concepts
- Art and Generative AI
- Prototyping Lab I: Environments
- Serious Game: Generative Systems for Worldbuilding
- Taxonavigating the Digital Space
- Vector Visions: Introduction to Image Processing and AI for Designers
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