Deep Learning On AWS

In this course, you’ll learn about AWS’s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works.

You’ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You’ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS.

This intermediate-level course is delivered through a mix of instructor-led training (ILT), hands-on labs, and group exercises.

• In this one-day course, you will learn cloud-based deep learning (DL) solutions on the AWS platform.
• You will learn how to run your models on the cloud using Amazon EC2‒based deep learning Amazon Machine Image (AMI) and Apache MXNet on AWS frameworks.
• In addition, you will learn how to use Amazon SageMaker and deploy your deep learning models using AWS services like AWS Lambda and Amazon Elastic Container Service (Amazon ECS)—all while designing intelligent systems on AWS.

This course teaches you how to:

• Define machine learning and deep learning.
• Identify the concepts in a deep learning ecosystem.
• Leverage Amazon SageMaker and MXNet programming framework for deep learning workloads.
• Fit AWS solutions for deep learning deployments.

This course is intended for:

• Developers responsible for developing Deep Learning applications
• Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS

We recommend that attendees of this course have the following prerequisites:

• Basic understanding of machine learning processes
• Basic understanding of AWS core services like Amazon EC2 and knowledge of AWS SDK
• Basic knowledge of a scripting language (e.g., Python)