Deep Learning on AWS Training

Course 1751

  • Duration: 1 day
  • Exam Voucher: Yes
  • Language: English
  • Level: Intermediate
Get This Course £660
  • 1-day instructor-led training course
#1751
  • Nov 11 9:00 AM - 5:00 PM GMT
    London or WebEx

Deep Learning on AWS is a one-day course that introduces you to cloud-based Deep Learning (DL) solutions on Amazon Web Services (AWS). The training will detail how deep learning is useful and explain its different concepts. This course also teaches you how to run your models on the cloud using Amazon SageMaker, Amazon Elastic Compute Cloud (Amazon EC2)-based Deep Learning Amazon Machine Image (AMI) and MXNet framework. In addition, you will gain a better understanding of deploying your deep learning models using AWS services like AWS Lambda and Amazon EC2 Container Service (Amazon ECS) while designing intelligent systems on AWS, based on Deep Learning.

    Deep Learning on AWS Training Delivery Methods

    • Official AWS training curriculum

    • Attend in-class or online

    Deep Learning on AWS Training Course Benefits

    • 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

    AWS Deep Learning Course Outline

    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

    Who should attend this course?

    • 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

    Module 1: Machine learning overview

    • 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

    Module 2: Introduction to deep learning

    • 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

    Module 3: Introduction to Apache MXNet

    • 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

    Module 4: ML and DL architectures on AWS

    • 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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