Artificial Intelligence

Carnegie Mellon has led the world in artificial intelligence education and innovation since the field was created. CMU’s undergraduate Artificial Intelligence Program was the first of its kind in the United States, and is the first Bachelor of Science in Artificial Intelligence offered in Qatar.

Artificial Intelligence at Carnegie Mellon

Introduced at Carnegie Mellon’s Pittsburgh campus in 2018, and at the Qatar campus in 2025, the Bachelor of Science in Artificial Intelligence (BSAI) program provides students with the expertise in machine learning and automated reasoning to build the AI of tomorrow.

Artificial intelligence represents a broad and dynamic field, and at Carnegie Mellon University, we embrace our role in shaping its future. We offer a broad and deep curriculum that reflects the impact of AI on careers and the skills needed to thrive in a tech economy.

Artificial Intelligence students have identical graduation requirements as students at Carnegie Mellon in Pittsburgh. Graduates have CMU degrees, conferred from the U.S. campus.

Students who would like to study Artificial Intelligence or Computer Science apply to a common Computing at CMU-Q year without declaring a major. At the end of the first academic year, Computing at CMU-Q students will declare a major of either AI or CS.

Learn more about applying to AI or CS

Program at a Glance

The AI Program gives students the in-depth knowledge to transform large amounts of data into actionable decisions. The curriculum focuses on how complex inputs — such as vision, language and huge databases — can be used to make decisions or enhance human capabilities.

The Artificial Intelligence Program at CMU-Q includes:

AI core and electives
Mathematics and statistics core
Computer science core
University core courses in general education
Ethics elective

Students at CMU-Q have many opportunities to engage in research, including a senior thesis project, independent study, or internships with a CMU-Q research group.

Program Details

Curriculum

The Bachelor of Science degree in Artificial Intelligence includes coursework in computer science, math, statistics, computational modeling, machine learning and symbolic computation. Because Carnegie Mellon is devoted to AI for social good, students also take courses in ethics and social responsibility, with the option to participate in independent study projects in areas like healthcare, transportation and education.

As students progress through the BSAI program, they develop critical thinking skills with respect to AI methods and applications. They learn to evaluate when and why to use each method, to propose modifications, and to build the AI of tomorrow.

Standard Completion Time: 4 Years
Minimum units required for degree: 360 units
- Mathematics: 71
- Computer science: 60
- Artificial Intelligence: 70
- Computer science electives: 18
- Ethics: 9
- Science and Engineering: 36
- Humanities and Arts: 63
- First Year Seminar and Core@CM: 6
- Free Electives: 27

See the CMU Undergraduate Catalog for more information about the requirements for a Bachelor of Science degree in Artificial Intelligence.

Learn more about the courses at CMU.

Areas of Study in Artificial Intelligence

CMU-Q first-year students in both the Artificial Intelligence Program and the Computer Science Program start with the same core computing background. Students in the BSAI program then focus their studies in several key areas.

Artificial Intelligence core

Explore how machines can learn, reason, and make decisions using techniques like machine learning and large language models (LLMs).

Decision Making and Robotics

Design and program intelligent machines that sense, move, and interact with their environment autonomously.

Machine Learning

Learn techniques that cover areas like deep learning, large-scale data analysis, generative AI, Bayesian methods, and optimization.

Perception and Language Cluster

Delve into how AI systems interpret and process sensory information, including search, speech, and computational approaches to vision and photography.

Human-Computer Interaction

Design and evaluate AI tools that are intuitive, effective, and centered around user needs and experiences.

Ethics

Examine the societal impacts, moral considerations, and policy challenges presented by artificial intelligence.

Projects and Research

Students in the Artificial Intelligence Program put their knowledge into practice through in-depth projects and research. This experience enhances learning and encourages creative problem-solving.

This is a small sample of course projects that CMU-Q students have worked on:

Hail to the Text: Transferring Political Styles for Enhanced Speech Generation
Enhancing Disordered Speech from Children Using Generative Adversarial Network and Speech Impairment Severity
Efficient Pre-training Techniques for Speech and Audio Large Language Models
Deep Learning in 3D: Enhancing Point Cloud Data for Real-World Applications

Artificial Intelligence Research

Carnegie Mellon University is a world leader in artificial intelligence research, and this research culture extends to the Qatar campus.

Exposure to cutting-edge research is critical for our BSAI students. Students at CMU-Q have many opportunities to engage in research: they can pursue a senior thesis, independent study guided by a faculty mentor, or an internship with one of the CMU-Q research groups.

Learn more about undergraduate research opportunities at CMU-Q

Arts and Sciences

Individualize your degree

Academic Support

Student Research and Innovation

Career Pathways

Graduates find work as artificial intelligence (AI) engineers, machine learning specialists, data scientists, cybersecurity engineers, roboticists or developers in areas like FinTech and business intelligence. They can also work in emerging fields such as language technology, computational biology, human-computer interaction and robotics.

Learn more about our graduates and where they are working to impact the world around them.

Meet the Faculty

Faculty members include experts in artificial intelligence, cloud computing, computational morphology, cybersecurity, database management systems, mobile and pervasive computing, natural language processing, parallel computer architectures, and wireless embedded systems.