Curriculum for AI Graduate Certificate
At the end of the three courses, students will have gained the foundational skills needed to effectively enter the field of AI Engineering, with a wide range of applications ranging from manufacturing, materials engineering, supply chain and logistics, healthcare systems, bioinformatics, chemical engineering, sustainable infrastructure planning and climate change adaption, etc.
For students who choose to, the preparation will allow them to explore more advanced topics through independent research or advanced curricula. All courses will be taught through an engineering problem solving lens.
Current graduate students in the College of Engineering and non-matriculating students with undergraduate degrees, and sufficient technical background, are eligible to apply.
Read more about the AI Engineering Graduate Certificate and the overarching AI Engineering Program.
We are committed to providing you with tailored guidance and support throughout the duration of your certificate program. Please direct any questions to Nauman Tazeem at ntazeem [at] umass [dot] edu (ntazeem[at]umass[dot]edu).
Requirements:
This certificate is formulated and sequenced to provide the foundation and structure (Core courses 1 and 2), and in-depth focus on specialized topics (Elective), while at the same time being flexible to cater to different student interests (multiple specialization categories for Elective).
Students are required to take one course from C1 (core course 1) and one from C2 (core course 2). Though students can take a C1 and a C2 in the same semester, it is recommended that they do it sequentially; while they are separate topics, a C1 course can better prepare students for a C2 course. Students can take an Elective course after C1 if it does not need C2.
Departments will collaborate to offer at least one course in Core 1, one in Core 2, and three in Electives every year.
(C1) Core Course 1 – Statistical Machine Learning for Engineers (pick ONLY one)
CEE 590ST Machine Learning Foundations and Applications
MIE 622 Predictive Analytics and Statistical Learning
(C2) Core Course 2 – Deep Learning for Engineers (pick ONLY one)
ECE 601: Machine Learning for Engineers
CEE 616: Probabilistic Machine Learning
MIE 690D: Deep Learning for Engineering Applications
Elective (pick AT LEAST one from any of the specialization categories)
AI/ML Methods
CEE 790ST: Advanced Probabilistic Machine Learning
MIE 624: Machine Learning for Dynamic Decision-Making
Engineering Applications
BME 615: AI in Biomedicine
ECE 627: Artificial Intelligence Based Wireless Network Design
ECE 629: Applied Machine Learning for the Internet of Things
MIE 659: Intelligent Manufacturing
MIE 650: Vehicle Automation
Hardware Design
ECE 662: Hardware Design for Machine Learning Systems
ECE 676: Neuromorphic Engineering
Signal Processing
ECE 746: Statistical Signal Processing
ECE 608: Signal Theory
BME 609: Biomedical Signals and Systems
Prerequisites:
Undergraduate level courses in the following. These courses are typical coursework of most undergraduate engineering programs. All but Linear Algebra are currently required of majors within the College of Engineering:
Linear algebra
Probability and statistics
Multivariate calculus
Programming (Python or R are typically used in the above courses; efficiency in programming to learn new packages or libraries would be necessary)
FAQs:
How to Apply? Please fill out the Intention to Complete the AI Engineering Graduate Certificate form. It is mandatory to submit the form before enrolling in your first course for the AI Engineering Certificate.
Am I eligible to pursue the certificate? You must be registered at UMass Amherst as a graduate student or a non-degree graduate student before completing this form. We typically require that you have sufficient background in probability and statistics, multivariate calculus, and programming (Python or R). Background in Linear Algebra is preferred but not required.
What documents do I need to submit for the certificate? You will need to submit the certificate eligibility form in the semester you are completing the final certificate course(s). You only need to electronically complete Sections A and B. Please email the completed form by the stated deadline for each academic term to Nauman Tazeem at ntazeem [at] umass [dot] edu (ntazeem[at]umass[dot]edu).
When can I expect to receive my certificate? The timeline for receiving the certificate is same as that listed for the diploma, and the details can be found here.