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HeFDI Code School Expert Track - Workshop 1: Fundamentals of Deep Learning

A workshop track for researchers who already have experience with coding, but want to further develop their skills by diving into the vast field of code and AI.

Veranstaltungsdaten

About the HeFDI Code School Expert Track 

The HeFDI Code School Expert Track offers 2 online workshops in cooperation with hessian.AI. The workshop series is intended for researchers who already have experience with coding, but want to further develop their skills by diving into the vast field of code and AI.

For active participation in the workshops and to receive a certificate of attendance signed by NVIDIA, you must register with NVIDIA's Deep Learning Institute. Further details will be provided during registration. Please note that participation is limited to academic students, staff, and researchers.

About this workshop

Businesses worldwide are using artificial intelligence to solve their greatest challenges. Healthcare professionals use AI to enable more accurate, faster diagnoses in patients. Retail businesses use it to offer personalized customer shopping experiences. Automakers use it to make personal vehicles, shared mobility, and delivery services safer and more efficient. Deep learning is a powerful AI approach that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, and language translation. Using deep learning, computers can learn and recognize patterns from data that are considered too complex or subtle for expert-written software.

Topics covered

• PyTorch
• Convolutional Neural Networks (CNNS)
• Data Augmentation
• Transfer Learning
• Natural Language Processing

Prerequisites

In addition to possessing a basic knowledge of coding, please take a look at the following external information on preparation.

Registration

Please register here. Please note that participation is limited to academic students, staff, and researchers. When registering, ensure that your affiliation is clearly indicated through your email address.