1. Home
  2. Training Library
  3. Introduction to Applying Machine Learning and AI services on AWS Learning Path

Introduction

The course is part of this learning path

Applying Machine Learning and AI Services on AWS
course-steps 5 certification 1 lab-steps 2

Contents

keyboard_tab
Applying Machine Learning and AI services on AWS Learning Path
play-arrow
Start course
Overview
DifficultyBeginner
Duration3m
Students333

Description

This course provides a quick introduction to the "Applying Machine Learning and AI services on AWS” Learning Path.

This is an intermediate level learning path designed to familiarise yourself with Machine Learning and other AI related technologies available within the AWS platform.

The learning path will provide you with the necessary knowledge and skills to apply machine learning using various approaches, ranging from building a Distributed Machine Learning environment using EMR, to integrating Amazon Machine Learning application services such as Amazon Rekognition and Amazon Lex into your own applications.

Transcript

Hello and welcome to the "Working with Machine Learning and AI services on AWS" Learning Path. 

This is an intermediate level learning path designed to familiarize yourself with machine learning and other AI-related technologies available within the AWS platform. This learning path will provide you with the necessary knowledge and skills to apply machine learning using various approaches ranging from building a distributed machine learning environment using Elastic MapReduce, to integrating Amazon machine learning application services such as Amazon Rekognition and Amazon Lex into your own applications. 

We start with a course on distributed machine learning where we will show you how to build an EMI cluster with Apache Spark installed. We will train a decision tree machine learning model using MLlib and Scalar. We will integrate other services and tools into our solution such as Athena, S3, and AWS Glue. 

We then continue with a hands-on lab where you'll be introduced to the Amazon Deep Learning AMI. You'll get to spin up an instance of this AMI and use the TensorFlow framework. 

We then move on to the first of the Amazon machine learning application services, Amazon Rekognition. Within this course, you'll learn about Amazon's managed computer vision service and how it can be integrated into your own applications. This course is followed by another hands-on lab in which you will build a serverless solution using Lambda and DynamoDB to perform object and feature extraction on image files stored within an S3 bucket. 

We then move on to the second of our Amazon machine learning application services, Amazon Lex. Within this course, you will learn about Amazon's managed service for building conversational interfaces and how it can be integrated into your own applications. 

Finally, we finish the learning path by providing an exam which helps you test your knowledge and readiness for developing with machine learning and AI services on the AWS platform. 

That concludes our learning path introduction. We really do hope you will enjoy and learn from this content.

About the Author

Students7309
Labs19
Courses52
Learning paths11

Jeremy is the DevOps Content Lead at Cloud Academy where he specializes in developing technical training documentation for DevOps.

He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 20+ years. In recent times, Jeremy has been focused on DevOps, Cloud, Security, and Machine Learning.

Jeremy holds professional certifications for both the AWS and GCP cloud platforms.