Course Details | Cloudthat

Course 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. The course comprises presentations, group exercises, and hands-on labs.

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

Upcoming Batches

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Key Features

  • Our 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

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 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

Our Top Trainers

Pavan Bhawsar

Pavan is a Microsoft Certified Trainer at CloudThat. He is an enthusiastic and passionate trainer, empathic observer towards the trending technologies with demonstrated skill in Azure and hybrid Cloud Administration. He has 6+ years of corporate experience, etc.

Vivek Kumar

Vivek has been involved in various large and complex projects with global clients. He has experience in AWS, GCP and Azure Cloud Platforms. He has experience in various software development fields like Image Processing, Web designing, Networking etc.

Jagadesh Gonnagar

He has been a part of several large and complex software development projects with global clients. He has worked in USA for over 11 years before relocating to India. He has expertise in Database design/development, Web development, etc.

Haris AK

Haris works as Cloud Solutions Architect in CloudThat technologies, being passionate about ever evolving technology. He is specialist on Docker, Kubernetes, Ansible, Git/Jenkins, Terraform and other DevOps Technologies. Haris Architects’ solutions on Cloud as well on-Premises using wide etc.

Devi Vara Prasad

A Microsoft Certified Trainer with more than 15+ years of Corporate, Online and Classroom Training Experience, well versed in AWS an Azure Cloud platform and have been delivering trainings for more than 5years. Also has a vast etc.

Ajay Kumar Lodha

Ajay is cloud obsessed and cloud addict, that's how he describes himself. Ajay has been working with all the major cloud computing platforms like AWS, Azure, and GCP for more than 5 years now. He is into etc.

Guruprasad Srinivasrao Venugopal

He is a Cloud enthusiast with demonstrated skills in Azure, AWS Hybrid-Cloud administration, Linux and DevOps. Alongside working on Azure Cloud deployment, administration and implementation, he is also engaged in planning, designing and executing various nice technology etc.

Prarthit Mehta

Prarthit has been involved in various large and complex projects with global clients. He has experience in Microsoft, MS office 365 & AWS Infrastructure technologies and Windows servers, designing Active Directory and managing various domain services. He etc.

Priyant Gupta

Priyant is working in the Microsoft Technology space for last 5 years and is sharing the knowledge gained on Azure Administration, Azure Data Engineering and Dynamics 365 CE Apps. He has trained 1000+ professionals as a corporate trainer at etc.

Lakhan Kriplani

He had involved in various client projects to set up infrastructure on Cloud for various Analytics applications, E-Commerce, setup CICD Pipeline using AWS services. He has experience in developing highly secure, scalable web applications using MVC architecture. etc.

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₹ 19900 + 18% GST

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