Hands-on Machine Learning with AWS and NVIDIA

More information about this Course

Projects involving machine learning (ML) can be difficult, time-consuming, and complicated. AWS and NVIDIA solve this challenge with fast, effective, and easy-to-use capabilities for your ML project.

This course is designed for ML practitioners, including data scientists and developers, who have a working knowledge of machine learning workflows. In this course, you will gain hands-on experience on building, training, and deploying scalable machine learning models with Amazon SageMaker and Amazon EC2 instances powered by NVIDIA GPUs. Amazon SageMaker helps data scientists and developers prepare, build, train, and deploy high-quality ML models quickly by bringing together a broad set of capabilities purpose-built for ML. Amazon EC2 instances powered by NVIDIA GPUs along with NVIDIA software offer high performance GPU-optimized instances in the cloud for efficient model training and cost effective model inference hosting.

In this course, you will first get an overview of Amazon SageMaker and NVIDIA GPUs. After that, you’ll get your hands-on experience by running an Amazon SageMaker notebook instance with a GPU. You will then learn how to prepare a dataset for model training, build a model, execute model training, and deploy and optimize the ML model. Additionally, you will gain hands-on experience applying this workflow to computer vision (CV) and NLP use cases. You will be able to build, train, deploy, and optimize ML workflows in Amazon SageMaker with GPU acceleration after completing this course. Additionally, you will comprehend the essential Amazon SageMaker services that are applicable to computer vision and NLP ML tasks.