April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course

Register for the FREE 2 day training course.

Deep Learning Fundamentals with PyTorch and FiftyOne
NVIDIA DLI Certification Workshop for Academia

April 5-6, 2025 | 10 AM – 5 PM CET

About the Workshop

Note: This course is only available to university students, researchers and teaching staff. A valid university email address is required to obtain a certificate.

This two day workshop is an extension of NVIDIA’s DLI Deep Learning Fundamentals Course.

Learn to implement neural networks for image classification from scratch using PyTorch. Learn about stochastic gradient descent, multilayer perceptrons, convolutional neural networks, and transformers. We will explore data augmentation, workflow management, and dataset curation using FiftyOne, a powerful open source tool for image dataset curation.

On the first day we will focus on building and training neural networks with PyTorch.

On the second day we will focus on visual dataset curation with FiftyOne and iterative improvement of image classification models.

Instructor

Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Antonio is a certified instructor of deep learning and diffusion models at NVIDIA’s Deep Learning Institute.

Prerequisites

• Programming Prerequisites: Python fundamentals
• Mathematics Prerequisites: Statistics and probability, linear algebra, calculus

Technologies Used in the Workshop

• Python
• Jupyter
• PyTorch
• Pandas
• FiftyOne
• Google Colab
• Github Codespaces

Assessment Type

Skills-based coding assessments evaluate students’ ability to train a deep learning model to classify images with high accuracy.

Certificate

Upon successful completion of the coding assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

Hardware Requirements

Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud.

Language

English