Elevate your machine learning skills with our comprehensive course, "Graph Neural Network". This course covers everything you need to know about graph neural network models, including the basics of graph machine learning, advanced graph neural networks with various mechanisms, and how to leverage these models to address specific real-world problems.

In this course, you will engage in hands-on activities and solve real-world problems such as in image recognition and time-series prediction, while receiving expert guidance from our instructors. By the end of this course, you'll have the knowledge and confidence to tackle any machine-learning challenge using graph neural networks. Join us and become a leader in the AI field!

This course is one of 6 courses in the Advanced AI Techniques pilot micro-credential pathway offered by the Translational AI Center at Iowa State University. For more information regarding the course including: Learning Outcomes, Assessments, and a Course Outline please visit the Graph Neural Network course page from Iowa State Online.

Prerequisites

• Basic Python programming
• Basic understanding of deep learning
• Basic understanding of graphical concepts
• Basic PyTorch programming

Intended Audience
The course is intended for a broad audience within the spectrum of the software and technology industry, including software engineers, data scientists, data engineers, data analysts, research scientists, and software developers. The course is designed to provide a basic understanding of AI and how to use PyTorch for a broad range of audiences.