Many of the most important real-world impacts will come from figuring out how to employ Artificial Intelligence (AI) algorithms into physical systems. This integration challenge is immense, and the innovative systems we design must prove to be resilient, trustworthy and secure.
Carnegie Mellon University’s College of Engineering is equipping next generation engineers with the ability to integrate AI into the constraints of the engineering problem and view the challenge from a new perspective by way of seven new master’s degrees in AI Engineering and one additional degree at CMU-Africa
“CMU is well-positioned to offer these programs because not only are we a world-class engineering college, but we have a vast wealth of expertise amongst faculty using AI and computing within their engineering research,” explained Shelley Anna, associate dean for faculty and graduate affairs and strategic initiatives. “This enables students to work with award-winning faculty who understand how to blend AI and engineering together. We encourage our students to take advantage of those collaborative approaches that are taking place across campus.”
Experts from our biomedical, chemical, civil and environmental, electrical and computer, materials science, and mechanical engineering departments have come together with CMU Africa and the Information Networking Institute to create the new master’s degree programs. The inaugural class enrolled in fall 2022.
Minkwon Choi decided to pursue a Master of Science in Artificial Intelligence Engineering - Electrical and Computer Engineering degree because he recognized that AI is shaping tomorrow. “AI is all around us. I want to bring my engineering knowledge into AI so that I can do something amazing with it.”
Students in the Master of Science in Artificial Intelligence Engineering programs are immersed in courses that blend engineering domain knowledge and the fundamentals of AI and machine learning.
The programs have four core courses across disciplines: Systems & Tool Chains for AI Engineers, Introduction to Machine Learning for Engineers, Introduction to Deep Learning for Engineers, and Trustworthy AI Engineering to give students a foundational understanding of AI Engineering.
Each discipline also has a unique integration approach whether that be a required research project or a project-oriented course that integrates the two approaches. The combination of domain knowledge and AI fundamentals help them to discover enhanced and breakthrough solutions to the entire engineering process.
We are creating an opportunity for our students to define a unique career.Shelley Anna, Associate Dean for Faculty and Graduate Affairs and Strategic Initiatives, College of Engineering
“You can’t open the newspaper without seeing something about how AI is embedding itself within the design of all sorts of physical systems. Even the phone in your pocket is running on AI.” Anna shared. “Our students will end up working for companies that want to use AI to move their business forward. Whether that be developing autonomous systems for self-driving cars or enabling a chemical plant to make decisions to optimize operations, our students will be prepared with a deep expertise in both AI and engineering. We are creating an opportunity for our students to define a unique career.”