March 3
@
8:00 am
–
March 30
@
5:00 pm
In this course, “Parallelism in Deep Learning,” you will learn about the need for parallelism in deep learning and how to use different methods of parallelism in deep learning. You will also learn about leveraging data parallelism and model parallelism workflows for your AI models on HPC infrastructures.
In this course, you will engage in hands-on activities, homework, and instructor consulting to make learning parallelism in deep learning enjoyable and rewarding. You will also be able to tackle real-world model training problems on HPC clusters. By the end of this course, you’ll have the skills and confidence to train your AI models at scale using multiple GPUs and nodes.
Complete any 3 courses listed below to earn the Advanced AI Techniques badge:
- Basic Python programming
- Basic understanding of deep learning
- Basic PyTorch programming
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 high-performance computing for deep learning and how to use these models for a broad range of audiences.
The course starts on March 3, 2025. All coursework must be completed by April 30, 2025, in order to earn the micro-credential badge. You will continue to have access to the course materials until January 1, 2026. The approximate time to complete this course is 16 hours.
This course has an instructional period from March 3 to March 30, 2025. During this instructional period, course materials will be released weekly and live synchronous sessions will be held. You may complete the course materials at your own pace. Live Zoom meetings will be conducted for interactive coding sessions. A suitable time for these live sessions will be determined through a group poll. The recordings of those sessions will be available soon after each meeting.
You will receive the Parallelism in Deep Learning micro-credential badge upon successful completion of the course assessments.
Registration for TrAC microcredential courses would be as an independent study course with 1 credit per course. Any of the courses in the series are available for credit (each 1 credit and a maximum of 3 credits per semester) as an independent study (ME 590Z) under Dr. Aditya Balu. Students must register for the independent study by emailing benearl@iastate.edu and cc-ing baditya@iastate.edu. Also, fill this google form for our records: https://forms.gle/X615ftuW2cC9NQfj8
Industry Professionals/ISU Staff/Postdocs, etc.:
Industry professionals, ISU Staff, and Postdocs can register to this course as non-credit microcredential badge only through ISU Online for an introductory promo price of $500.
Price: $500 Initial Promo Discounted price (ISU Professionals/Staff and government employees pay $300)
