Relus Cloud Webinars

 

Amazon machine learning quick start & use cases

AI, ML and IOT are hot buzzwords today and given the hype, many companies are trying to grapple with what this means to their business. This webinar will introduce both current and future AWS customers to the practical approach of laying the foundation of your business applications with analytics and then leveraging artificial intelligence (AI) and machine learning (ML) to make your business more intelligent.

In this webinar, attendees will learn:

  • Various AWS service launches that provide developers with the ability to add intelligence to their applications
  • In depth case studies of customers who are leveraging Amazon ML and other advanced ML capabilities of AWS

Recipe for a quick & successful cloud migration

Preparing for the Retail Season in AWS

 
 

 

AWS Business Value Videos

AWS Platform Overview

Amazon Web Services provides cost-effective, scalable, and secure infrastructure for all businesses.

Extending Infrastructure with AWS

This webinar covers the key benefits of extending your infrastructure to Amazon Web Services.

AWS Product Overview Videos

Introduction to Amazon EC2

Learn tricks and hear tips you can implement to reduce waste and fine-tune your spending with AWS.

Introduction to Amazon DynamoDB

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.

Introduction to Amazon RedShift

Amazon RedShift is a powerful, fast and fully-managed data warehouse service that works with your existing analytics tools.

Introduction to Amazon S3

Amazon Simple Storage Service (Amazon S3), provides developers and IT teams with secure, durable, highly-scalable object storage. 

Introduction to Amazon Kinesis

Amazon Kinesis is a fully managed service for real-time processing of streaming data at any scale. 

Introduction to Amazon Elastic MapReduce

Amazon Elastic MapReduce (Amazon EMR) is a web service that makes it easy to quickly and cost-effectively process vast amounts of data.