Deep Learning on AWS
You will 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 classroom 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.
1 Day / 8 Hours
Live Class
Certificate on completion
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
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
Intended Audience
You can take on this AWS course if you belong to the following category of individuals:
- Developers 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
Activities
This Deep Learning On AWS Training will include the following activities:
- Live Demonstrations
- Group Discussions
- Hands-On Labs
- Knowledge Checks
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
Talk to a Learning Advisor
FAQs
Yes, we are an AWS Advanced Tier Training Partner
Anyone who wants to start a profession in AWS cloud is fit to enroll in this course. No prior knowledge of coding or other technical skills is required.
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.
You may reach out at the contact number listed on our official website or write to us at info@cloudwizard.wpenginepowered.com.
Wire Transfer, Credit Card, Debit Card, UPI & Purchase Order
There is no minimum number of candidates required, we are happy to train 1 to 1 should you wish. With regard to the maximum number, we can accommodate 30 learners in one batch.
1. Training delivered by an Amazon Authorised Instructor
2. AWS Content E-Kit
3. Hands-on labs- 30 days
4. Class attendance certificate
You will get the access to course content & lab on first day of your training session.
The course completion certificate will be issued to your email id within 2 weeks of completing your course.
A one-day course could be delivered over two half day sessions (4 hours a day), or a three-day course could be delivered over five days (4 hours a day).
MOBILE LAYOUT
Deep Learning on AWS
1 Day / 8 Hours
Live Class
Certificate on completion
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
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