M.S. in Artificial Intelligence Engineering - Mechanical Engineering (120 units)
Within the discipline of Mechanical Engineering, students will learn how to design and build AI-orchestrated systems capable of operating within engineering constraints. At Carnegie Mellon University, we are leading this transformation by teaching students how to simultaneously design a system’s functionality and supporting AI mechanisms, including both its AI algorithms and the platform on which the AI runs, to produce systems that are more adaptable, resilient, and trustworthy. The program is three semesters long.
Students pursuing the M.S. in AI Engineering - Mechanical Engineering will be able to:
- Apply deeper knowledge of AI methods, systems, tool chains, and cross-cutting issues including security, privacy and other ethical and societal challenges
- Identify the engineering constraints that AI-orchestrated systems must operate within
- Solve practical problems using AI methods
- Adapt to the latest AI-enabled tools and learn how to work with and “advise” machines
- Demonstrate graduate-level domain knowledge in mechanical engineering
Students with a bachelor’s degree in mechanical engineering or a related discipline with an interest in the intersection of AI and engineering are encouraged to apply to this program.
Students should be able to demonstrate proficiency in:
- Programming (Python preferred) for data analysis
- Probability/statistics such as probability distributions, joint and conditional probability, independence, marginalization, Bayes rules, and maximum likelihood estimation
- Linear algebra topics such as matrix operations, linear transformations, projections, matrix derivatives, and eigendecomposition
English proficiency is required for non-native English speaking applicants.
The M.S. in Artificial Intelligence Engineering - Mechanical Engineering program is completed in three semesters with 120 units of coursework and the completion of a capstone research project. In addition to core and domain courses, students will complete graduate-level mechanical engineering courses, professional development units, technical electives, and College of Engineering units.
Systems and Tool Chains for AI Engineering
Introduction to Machine Learning for Engineers
Introduction to Deep Learning for Engineers
Design and Manufacturing of Mechanical Systems
Energy and Thermal Fluid Systems
Robotic and Control Systems
Whether pursuing academia or industry, this degree uniquely positions students for the future of research and high demand careers with a mastery of integrating engineering domain knowledge into AI solutions.
Each of our master’s programs provides:
- hands-on learning and collaborative problem-solving through project-based courses
- flexibility to tailor your curriculum according to your interests and goals
- ongoing services and programming to enhance communication, leadership, and team-building skills in the Carnegie Mellon and Pittsburgh ecosystems
- personalized career advising services and networking opportunities to ensure your long term professional success.
Our master’s programs are self-supported or have an outside funding source (such as the student’s employer) to pay for tuition and living expenses. To see annual tuition rates, visit Carnegie Mellon’s The HUB website
Note that immigration regulations do not allow Carnegie Mellon University to issue visa documents for part-time master’s programs.