Deep Learning on AWS (AWSDL)

Course 1751

  • Duration: 1 day
  • Language: English
  • Level: Intermediate
Get This Course 8.400 kr
  • 1-day instructor-led training course
  • Official AWS training curriculum

#1751

Deep Learning ILT introduces you to cloud-based deep learning solutions on AWS. In this course, we will detail how deep learning is useful and explain the different concepts in deep learning. This course also teaches you how to run your models on the cloud using Amazon EC2-based Deep Learning AMI and MXNet framework. This course will help you gain a better understanding of deploying your deep learning models using AWS services like AWS Lambda, and Amazon EC2 Container Service (ECS) while designing intelligent systems on AWS based on deep learning.

    Deep Learning on AWS (AWSDL) Delivery Methods

    • In-Person

    • Online

    Deep Learning on AWS (AWSDL) Course Information

    • In this Deep Learning on AWS (AWSDL) course, you will learn 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.
    • Deep Learning on AWS (AWSDL) Prerequisites

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

      • Basic understanding of ML processes
      • Basic understanding of AWS core services like EC2 and knowledge of AWS SDK
      • Basic knowledge of a scripting language e.g. Python

    Deep Learning on AWS (AWSDL) Course Outline

    • A brief history of AI, ML, and DL
    • The business importance of ML
    • Common challenges in ML
    • Different types of ML problems and tasks
    • AI on AWS
    • Introduction to DL
    • The DL concepts
    • A summary of how to train DL models on AWS
    • Introduction to Amazon SageMaker
    • Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model
    • The motivation for and benefits of using MXNet and Gluon
    • Important terms and APIs used in MXNet
    • Convolutional neural networks (CNN) architecture
    • Hands-on lab: Training a CNN on a CIFAR-10 dataset
    • AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk)
    • Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition)
    • Hands-on lab: Deploying a trained model for prediction on AWS Lambda

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    Deep Learning on AWS (AWSDL) Course FAQs

    This course is intended for:

    • Developers responsible for developing DL applications
    • Developers who want to understand the concepts behind deep learning and how to implement a DL solution on AWS

    Yes! We know your busy work schedule may prevent you from getting to one of our classrooms which is why we offer convenient online training to meet your needs wherever you want.