Fundamentals in AI Graduate Certificate
BUILD AI SKILLS NOW — GRADUATE WITH AN EDGE
By completing the Fundamentals of AI Certificate, you’ll graduate already prepared with the in-demand AI skills employers expect for technical roles across industries and in your area of study.
Open to all undergraduate and graduate students.
Available as a stand-alone credential or supplement to your current program of study.
Choose from eleven career-focused specializations.
What You’ll Learn:
Fundamental theory, technical algorithms, and engineering applications in the general areas of artificial engineering, machine learning and deep learning
Apply AI skills specifically in your technical area of study or professional interest
Program Structure
Total credits: 9 (or 12) credits depending on departmental requirement
Two core courses and one or two program or department-specific courses
Curriculum
Core AI Courses | Students Choose One Course Per Row
Core course 1* | AAI 551 - Engineering Programming: Python | CS 515 - Intro to CS OR CS 541 - AI |
Core course 2 | AAI 595 - Applied Machine Learning | CS 559 - Machine Learning |
*If the student has sufficient programming background/experience, CS 508 - Human-Centered AI can be used for core course 1
Department-Specific Coursework and Required Courses
Graduate Certificate Title | Required Coursework |
|---|---|
BME 571 - Machine Learning in Biomedical Engineering | |
CE 546 - Machine Learning and Analytics in Civil Engineering Applications | |
CH 564 - AI/ML Enabled Drug Discovery and Synthesis | |
Fundamentals in AI for Chemical Engineering / Materials Science | Select one: CHE 542 - Data Science in Pharmaceutical Development CHE 543 - Machine Learning in Pharmaceutical Development CHE 685 - AI & Machine Learning for Industrial Applications: Innovations in Rheology and Material Processing |
CS 583 - Deep Learning | |
AAI 628 - Deep Learning Engineering: from Neural Networks to LLMs | |
Fundamentals in AI for Engineering Management / Systems Engineering | Select one: MA 549 - Logical Knowledge Representation and Reasoning MA 610 - Artificial Intelligence in Mathematical Research MA 661 - Dynamic Programming and Reinforcement Learning MA 663 - Computational Learning Theory and Reasoning |
ME 596 - Machine Learning in Mechanical Engineering | |
PEP 559 - Machine Learning in Quantum Physics | |
SSW 625 - AI for Software Engineering | |
BIA 568 - Management of AI Technologies |