AI Engineering Fundamentals - Online Graduate Certificate
An online program for engineers who want cutting-edge skills in AI, machine learning and deep learning.
Download the Program Spec Sheet
Learn more about the curriculum, course format, financing options, and program faculty.
Program Highlights
9 Months (2 Semesters)
Start in Fall or Spring
2 Grad-Level Courses
AI & ML for Engineers
Deep Learning for Engineers
Delivered 100% Online
Via Zoom and Canvas LMS
Financing Options
Monthly Payment Plans
Partial Tuition Fellowships
G.I. Bill Eligible
Key Features
Taught Live-Online by CMU Faculty
in CMU’s College of Engineering, ranked #7 in the nation for graduate engineering programs.
Designed for Working Professionals
with weekly, live-online sessions in the evening (ET) and asynchronous coursework you can finish on your own time, at your own pace.
Engaging Educational Experiences
that go beyond recorded lectures. Active learning sessions will help you master key concepts so you can immediately apply them at work.
Built for Your Busy Life. Designed to Make an Impact.
CMU’s AI Engineering Fundamentals certificate offers the rigor of a graduate-level education with the flexibility you need to make strides in your career.
When you enroll in our certificate, you can expect:
- Evening, live-online sessions taught by CMU College of Engineering faculty
- Self-paced assignments to fit your schedule
- Real-time collaboration with a diverse network of peers
- Personalized support throughout your learning journey
At Carnegie Mellon, we're passionate about bringing CMU signature content to working professionals around the country. Learn how we make this happen from CMU's Vice Provost for Teaching and Learning Innovation, Dr. Marsha Lovett.
Meet Our World-Class Faculty
Dr. Levent Burak Kara
Professor of Mechanical Engineering
Education: Ph.D., Carnegie Mellon University
Research Focus: Developing new computational analysis, design, and manufacturing technologies with wide-ranging applications in areas like mechanical CAD, topology optimization, additive manufacturing, electronics design, and bio-engineering. In his research, Dr. Kara combines principles of machine learning, optimization, and geometric modeling to develop new knowledge and computational software for use in next-generation design systems.
Dr. Amir Barati Farimani
Associate Professor of Mechanical Engineering
Education: Ph.D., University of Illinois at Urbana-Champaign
Research Focus: Applying machine learning, data science, and molecular dynamics simulations to health and bio-engineering problems. Dr. Farimani’s lab unites researchers with different backgrounds (including physics, materials science, mechanical engineering, bio-engineering, chemical engineering, and computer science) to bring the state-of-the-art machine learning algorithm to mechanical engineering.
Want more info about the program? Download our Program Spec Sheet. Or, if you're ready to apply, start your application today!