Course Overview

This AWS Deep Learning training course from CloudThat offers candidates an in-depth understanding of AWS deep learning solutions, including scenarios on how deep learning works and where deep learning makes sense. Taking up this Deep Learning on AWS training, candidates also learn how to run deep learning models in the cloud with the help of Amazon SageMaker and the MXNet framework. In addition, this Deep Learning on AWS certification course teaches candidates how to deploy deep learning models using services like AWS Lambda to design intelligent systems on AWS. The course comprises presentations, hands-on labs, and group exercises.

After completing this course, students will be able to:

  • 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 deployment

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Key Features

  • Our AWS Deep Learning certification training modules have 50% - 60% hands-on lab sessions to encourage Thinking-Based Learning (TBL).
  • Interactive-rich virtual and face-to-face classroom teaching to inculcate Problem-Based Learning (PBL).
  • AWS certified instructor-led training and mentoring sessions to develop Competency-Based Learning (CBL).
  • Well-structured use-cases to simulate challenges encountered in a Real-World environment.
  • Being an authorized AWS Training Partner gives us an edge over competition.
  • Integrated teaching assistance and support through experts designed Learning Management System (LMS) and ExamReady platform.

Who Should Attend

  • 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 Deep Learning on AWS 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

Course Outline Download 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 multilayer 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

Certification

    • By earning Deep Learning on AWS certification, you will show your future or current employer that you have knowledge of AWS Cloud concepts.
    • Deep Learning on AWS certification can be used to learn skills of deep learning in the AWS environment.
    • On successful completion of Deep Learning on AWS certification training aspirants receive a Course Completion Certificate from us.
    • By successfully clearing the Deep Learning on AWS certification exams, aspirants earn AWS Certification.

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Course ID: 13500

Course Price at

₹29900 + 18% GST

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