This training is specifically designed for ML engineers, data scientists, researchers and CTOs at healthcare and life sciences startups who are responsible for building, training, and deploying ML models to solve critical problems in drug discovery, medical imaging analysis, genomics research, personalized medicine, etc. In this training you will learn how HyperPod's high-performance capabilities enable efficient training of deep learning models on complex and intricate datasets, leading to improved accuracy and faster analysis. HyperPod can also significantly reduce training times (upto 40%) for complex models, allowing for faster iteration and discovery cycles.

The session will begin with an introduction to the specific features and benefits of SageMaker HyperPod, highlighting its scalability and performance advantages for tackling large-scale ML workloads. The core of the session will be a hands-on workshop where you'll gain practical experience using HyperPod. Next, we'll explore real-world use cases where HyperPod has been successfully implemented by healthcare and life sciences startups. Finally, we'll delve into best practices for optimizing your HyperPod training jobs. This will cover techniques for maximizing efficiency, minimizing costs, and ensuring the smooth running of your ML workflows on HyperPod.

Agenda:

2:00PM - 2:15 PM Intro HCLS Startup BD and benefits of HyperPod
2:15PM - 3:10PM Hands-on Sagemaker HyperPod workshop
3:10PM - 3:25PM Real world use cases with HyperPod
3:25PM - 3:30PM Participant survey and next steps