TrAC Advanced AI course on Graph Neural Networks

In this course, “Graph Neural Network”, we will learn about graph neural network models, a branch for machine learning and AI. We will cover everything from the overview of graph machine learning, basic graph neural networks and advanced graph neural networks with different mechanisms. We will also cover how to leverage these models to address specific real-world problems.

We’ve packed in plenty of hands-on activities, homework, and instructor consulting to make learning graph neural networks enjoyable and rewarding. You will also be able to tackle real-world problems, from image recognition to time-series prediction. By the end of this course, you’ll have the skills and confidence to tackle any machine-learning challenge with graph neural networks.

This course is one of a series of courses from the Translational AI Center (link) at Iowa State University.

Prerequisite

Intended Audience

The course is intended for a broad audience within the software and technology industry spectrum, including software engineers, data scientists, data engineers, data analysts, research scientists, and software developers. The course is designed to provide a basic understanding of graph neural networks and how to use these models for a broad range of audiences.

Expertise level: Intermediate/Advanced

Students: For credit

Any of the courses in the series are available for credit (each 1 credit and maximum 3 credits per semester) as an independent study (ME 590Z) under Dr. Aditya Balu. Interested students can register for the independent study by emailing benearl@iastate.edu and cc-ing baditya@iastate.edu. Also, please fill out the forms for our records: https://forms.gle/dBYXVjhdFLxbLepL6

Industry Professionals/ISU Staff/Postdocs, etc.: non-credit through ISU Online for an introductory promo price of $500.

Registration for Industry professionals: Link coming soon