AWS-DEEPL - Deep Learning on AWS

n 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.

Duration: 1.0 day

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Schedule

Virtual ILT | 22 Apr 2024 - 22 Apr 2024 India
Virtual ILT | 22 Apr 2024 - 22 Apr 2024 Sri Lanka
Virtual ILT | 22 Apr 2024 - 22 Apr 2024 United Arab Emirates

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Objectives

  • Learn how to define machine learning (ML) and deep learning
  • Learn how to 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

Content

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 Sage Maker
  • Hands-on lab: Spinning up an Amazon Sage Maker notebook instance and running a multilayer perceptron neural network model

Module 3: Introduction to Apache MX Net

  • The motivation for and benefits of using MX Net and Gluon
  • Important terms and APIs used in MX Net
  • 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 Recognition)
  • Hands-on lab: Deploying a trained model for prediction on AWS Lambda

Audience

This course is intended for:

  • 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

We recommend that attendees of this course have:

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

Certification

product-certification
This course is not associated with any Certification.

Course Benefits

product-benefits
  • Career growth
  • Broad Career opportunities
  • Worldwide recognition from leaders
  • Up-to Date technical skills
  • Popular Certification Badges

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