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Deep Learning on AWS

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In this course, you will learn about deep learning on AWS solutions, use cases for deep learning, and its guiding principles. You'll learn how to run deep learning models in the cloud using Amazon SageMaker and the MXNet framework. You'll learn how to use resources like AWS Lambda to run your deep learning algorithms as you build intelligent systems on AWS.

Course description

You will learn about deep learning on AWS solutions in this course, as well as use cases for deep learning and its principles. You’ll discover how to use Amazon SageMaker and the MXNet framework to run deep learning models in the cloud. While creating intelligent systems on AWS, you’ll also learn how to use tools like AWS Lambda to execute your deep learning algorithms.

Activities

This Deep Learning On AWS Training will include the following activities: 

  • Live Demonstrations 
  • Group Discussions 
  • Hands-On Labs 
  • Knowledge Checks

Course Objectives

Here’s what you’ll learn in this AWS course: 

  • Learn the definitions of deep learning and machine learning. 
  • Acquire knowledge on how to recognize the ideas in a deep learning ecosystem. 
  • Use the MXNet programming framework with Amazon SageMaker for deep learning workloads. 
  • Appropriate AWS setups for deep learning

Intended Audience

You can take on this AWS course if you belong to the following category of individuals:

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

Prerequisites

To qualify for taking up this AWS training, you’ll need the following:

  • A basic knowledge of ML processes
  • Knowledge of AWS core services like Amazon EC2 and AWS SDK
  • Knowledge of a scripting language like Python

Module Breakdown

Course outline

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 multilayer 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

FAQ's

Is Cloud Wizard Consulting an official AWS training partner?

Yes, we have been since 2015.

Who should take up this course?

You can take on this AWS course if you belong to the following category of individuals:

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

What prior experience do you need for this course?

To qualify for taking up this AWS training, you’ll need the following:

  • A basic knowledge of ML processes
  • Knowledge of AWS core services like Amazon EC2 and AWS SDK
  • Knowledge of a scripting language like Python

How do I enroll in this course?

To enroll in this course, choose the starting date and make an online payment. Once your payment is confirmed, our team will reach out to you.

Course Schedule

Course Name Date Register
Deep Learning on AWS 16 Dec - 16 Dec Register

Course Overview

Duration 1D / 8 HRS
Modality ViLT/ Classroom
Data Sheet DOWNLOAD
Check Dates CLICK HERE
Price 14,500.00

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