The Deep Learning on AWS training course is designed to demonstrate AWS's deep learning solutions, including scenarios where deep learning makes sense and how deep learning works.
The course begins by exploring how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. Next, it analyzes how to deploy deep learning models using services like AWS Lambda. The course concludes by illustrating how to design intelligent systems on AWS.
Prerequisites:
- ML processes
- AWS core services like Amazon EC2 and knowledge of AWS SDK
- A scripting language like Python
AWS Authorized Training is only available in Argentina, Brazil, Canada, Chile, Colombia, Costa Rica, Mexico, United States, and Peru.
THIS COURSE IS NOT ELIGIBLE FOR TRAINING BUNDLES.
Purpose
| Demonstrate AWS's deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. |
Audience
| Machine learning practitioners who are preparing to take the AWS Certified Machine Learning - Specialty exam. |
Role
| Software Developer |
Skill Level
| Intermediate |
Style
| Workshops |
Duration
| 1 Day |
Related Technologies
| Cloud Computing Training | AWS |
Productivity Objectives
- Define machine learning (ML) and deep learning
- Identify the concepts in a deep learning ecosystem
- Utilize Amazon SageMaker and the MXNet programming framework for deep learning workloads
- Incorporate AWS solutions for deep learning deployments