Carnegie Mellon University

Overview

The Master of Science in Artificial Intelligence Engineering (Materials Science & Engineering) at Carnegie Mellon University equips students with the skills needed to design and implement AI-enabled engineering systems that perform reliably under real-world conditions. This program merges artificial intelligence techniques with computational materials science, enabling students to create models and workflows that facilitate dependable decision-making in various engineering applications.

What you'll study

Core coursework themes

• AI engineering systems: Learn to construct AI-enabled systems utilizing suitable toolchains, software engineering best practices, and designs that account for deployment considerations.
• Trustworthy AI: Explore techniques to assess and enhance the reliability, robustness, and ethical behavior of AI systems.
• Computational materials science: Delve into modeling and simulation techniques employed in materials research, integrated with contemporary AI workflows.
• Machine learning for engineers: Gain hands-on experience with practical machine learning and deep learning methods, focusing on engineering constraints and assessment techniques.

Example courses include:

• Systems and Tool Chains for AI Engineering
• Trustworthy AI
• Methods of Computational Materials Science
• Deep Learning for Engineers
• Machine Learning for Engineers

Capstone / thesis:

Students will engage in a capstone project or thesis, tailored to their specific track and academic requirements. It is advisable to consult with the department for detailed expectations and guidelines.

Entry requirements

While GRE/GMAT scores and specific GPA cut-offs are not mandated, applicants should satisfy Carnegie Mellon University’s general graduate admission criteria and be prepared for advanced coursework in artificial intelligence and engineering disciplines.

Career prospects

Graduates of the program will be well-prepared for a variety of roles in industries where artificial intelligence and materials science intersect. Potential career paths include positions in research and development, data analysis, engineering design, and technology consulting, among others. The skills acquired in this program will be applicable across sectors, including manufacturing, aerospace, and information technology.