Deep Learning on AWS

1 800 U Learn (853 276)

Length

1 day

Price

$935.00 inc GST

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Overview

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.

Please note: students are required to bring their own laptop/tablet and power cable for this course.

Key Topics

Detailed Info

Machine learning overview
Introduction to deep learning
Introduction to Apache MXNet
ML and DL architectures on AWS

Skills Gained

Key Topics

Target Audience

Prerequisites

Skills Gained

This course is designed to teach participants how to:

Define machine learning (ML) and deep learning
Identify the concepts in a deep learning ecosystem
Use Amazon SageMaker and the MXNet programming framework for deep learning workloads
Fit AWS solutions for deep learning deployments

Key Topics

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

Please note: This is an emerging technology course. Course outline is subject to change as needed.

Target Audience

This course is intended for:

Developers who are 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

Prerequisites

It is recommended that attendees have the following prerequisites:

Basic understanding of machine learning (ML) processes
Basic understanding of AWS core services like Amazon EC2 and knowledge of AWS SDK
Basic knowledge of a scripting language like Python

We can also deliver and customise this training course for larger groups – saving your organisation time, money and resources. For more information, please contact us on 1800 853 276.

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The supply of this course by DDLS is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.

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Virtual-Classroom

12 May - 12 May

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This course aligns to an AWS certification

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