BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Translational AI Center - ECPv6.15.17.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Translational AI Center
X-ORIGINAL-URL:https://trac-ai.iastate.edu
X-WR-CALDESC:Events for Translational AI Center
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Chicago
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:20240310T080000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:20241103T070000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:20250309T080000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:20251102T070000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:20260308T080000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:20261101T070000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250303T080000
DTEND;TZID=America/Chicago:20250330T170000
DTSTAMP:20260404T002205
CREATED:20250122T225140Z
LAST-MODIFIED:20250122T225142Z
UID:2130-1740988800-1743354000@trac-ai.iastate.edu
SUMMARY:Parallelism in Deep Learning
DESCRIPTION: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. \n\n\n\nIn 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. \n\n\n\nThis 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. \n\n\n\nComplete any 3 courses listed below to earn the Advanced AI Techniques badge: \n\n\n\n\nScientific Machine Learning (SciML)\n\n\n\nGraph Neural Network\n\n\n\nSelf-Supervised Learning\n\n\n\nParallelism in Deep Learning\n\n\n\n3D Vision – Nerfs & INRs\n\n\n\nReinforcement Learning\n\n\n\n\nLearn more about Micro-Credentials at Iowa State University! \n\n\n\nPrerequisites\n\n\n\n\nBasic Python programming\n\n\n\nBasic understanding of deep learning\n\n\n\nBasic PyTorch programming\n\n\n\n\nIntended Audience\n\n\n\nThe 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. \n\n\n\nCourse Procedures\n\n\n\nThe 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.  \n\n\n\nThis 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. \n\n\n\nYou will receive the Parallelism in Deep Learning micro-credential badge upon successful completion of the course assessments. \n\n\n\nExpertise level:\n\n\n\nIntermediate/Advanced \n\n\n\nRegistration\n\n\n\nStudents:  \n\n\n\nRegistration 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 \n\n\n\nIndustry Professionals/ISU Staff/Postdocs\, etc.:  \n\n\n\nIndustry 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. \n\n\n\nRegistration link: https://iowastateonline.iastate.edu/programs-and-courses/professional-development-courses/parallelism-in-deep-learning/ \n\n\n\nPrice: $500 Initial Promo Discounted price (ISU Professionals/Staff and government employees pay $300)
URL:https://trac-ai.iastate.edu/event/parallelism-in-deep-learning/
CATEGORIES:Courses
END:VEVENT
END:VCALENDAR