Self-Supervised Learning

Dive into the cutting-edge world of self-supervised learning (SSL) for computer vision in this dynamic and hands-on course. SSL is revolutionizing AI by enabling models to learn from vast amounts of unlabeled data, making it a true game-changer.

In this course, you'll explore popular SSL methods like SimCLR, MoCo, BYOL, and Vision Transformers (DINO), while gaining hands-on experience using PyTorch to build and train your own models. Engage in interactive coding sessions and apply SSL techniques to real-world datasets through project-based assessments, ensuring you gain both theoretical knowledge and practical expertise. Whether you're an AI enthusiast or a professional looking to advance your skills, this course will equip you with the tools to create more efficient and scalable computer vision models. Join us and be at the forefront of AI innovation!

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 Self-Supervised Learning course page from Iowa State Online.

Prerequisite

Python programming
Fundamental idea of Computer Vision

Intended Audience
This course is aimed at software engineers, data scientists, data engineers, data analysts, research scientists, and developers who wish to advance their understanding of computer vision. Previous participants have included professionals from leading technology and AgriTech companies.

Pages / Length: 5 modules
Publication Date: 11/2024

Format

Price

Canvas eCourse

$500.00

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Permanent link for this product: https://store.extension.iastate.edu/product/17076