Fundamentals of Deep Learning-Workshop1
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These are two NVIDIA workshops and attendees who have registered must attend both sessions, on March 31st and April 7th.
Fundamentals of Deep Learning is a hands-on workshop designed by NVIDIA that introduces how businesses use AI, particularly deep learning, to solve real-world challenges across industries such as healthcare, retail, and automotive. Participants learn the fundamentals of training deep learning models, including techniques such as data augmentation and transfer learning. Through practical exercises and a final project, students build models from scratch and leverage pre-trained models, with all hands-on modules running on NVIDIA-hosted cloud resources. Those who complete the project and assessments receive an NVIDIA certificate. Space is limited to 40 participants.
More information: https://www.nvidia.com/en-sg/training/instructor-led-workshops/fundamentals-of-deep-learning/
Date and Time
Location
Hosts
Registration
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- 205 Humber College Blvd
- 1502
- Toronto, Ontario
- Canada M9W 5L7
- Room Number: J134-NORTH BUILDING
- Contact Event Hosts
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Only by registration.
- Co-sponsored by Faculty of Science and Technology, Humber Polytechnic / NVIDIA
- Starts 10 February 2026 05:00 AM UTC
- Ends 24 March 2026 04:00 AM UTC
- No Admission Charge
Speakers
Dr. Ernest Namdar of NVIDIA
Biography:
Address:Canada
Ernest Namdar
Biography:
Ernest (Khashayar) Namdar is an AI researcher with over seven years of experience applying machine learning to medical imaging. He is a senior data analyst at the Hospital for Sick Children, a software engineering P.Eng. holder, and an NVIDIA Deep Learning Institute artificial intelligence (AI) ambassador in healthcare. Ernest completed his Ph.D. at the University of Toronto’s Institute of Medical Science, where he developed AI-based virtual biopsy pipelines for pediatric brain tumors to support non-invasive diagnosis and treatment planning. He is currently a Postdoctoral Fellow, working on multiple translational AI projects aimed at improving patient health outcomes through advanced data-driven technologies and clinical integration.
More information: https://ernestnamdar.com
Address:Canada
Agenda
Learning Objectives
By participating in this workshop, you’ll:
- Learn the fundamental techniques and tools required to train a deep learning model
- Gain experience with common deep learning data types and model architectures
- Enhance datasets through data augmentation to improve model accuracy
- Leverage transfer learning between models to achieve efficient results with less data and computation
- Build confidence to take on your own project with a modern deep learning frameworkhttps://www.nvidia.com/content/dam/en-zz/Solutions/deep-learning/deep-learning-education/dli-fundamentals-of-deep-learning-1369828-r3-web.pdf