Applying Machine Learning and AI Services on AWS

OverviewStepsAuthor
DifficultyIntermediate
Duration6h 1m
Students423

Description

Overview
This learning path demonstrates practical applications of AWS machine learning and Artificial Intelligence services using a blend of instructional learning and hands-on labs. At the conclusion of this learning path, you will be able to implement and experiment with Amazon Machine Learning platform and application services. 

Intended Audience
This learning path is suited to anyone interested in applying AWS Machine Learning and Artificial Intelligence platform and application services.

Learning Objectives
By completing this learning path you will be able to:

  • Explain and apply Amazon Machine Learning, Amazon Rekognition, Amazon Lex chatbots, AWS Deep Learning AMI's and Amazon Distributed Machine Learning services.
  • Explain and apply distributed machine learning with Apache Spark, Amazon EMR, Spark MLib, and AWS Glue.
  • Apply and build a TensorFlow machine learning model using the Amazon Deep Learning AMI. 
  • Automate image and video processing using the Amazon Recoknition API.

Prerequisites
Having an understanding of cloud concepts will help with your assimilation of this content. If you are new to cloud computing I suggest completing the Introduction to Machine Learning on AWS Learning Path first. 

Content
This learning path includes 5 hours of High Definition video, 2 hands-on labs, quizzes and an assessment exam.

Feedback
We welcome all feedback so please direct any comments or questions on this course to us at support@cloudacademy.com 

Certificate

Your certificate for this learning path
lock

Learning Path Steps

1 courses

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 availabl...

2 courses

Overview This training course begins with an introduction to the concepts of Distributed Machine Learning. We'll discuss the reasons as to why and when you should consider training your machine learning model within a distributed environment.  Apache Sp...

3 labs

Develop, visualize, serve, and consume a TensorFlow machine learning model using the Amazon Deep Learning AMI in this Lab.

4 courses

Overview In this course you'll learn about Amazon Rekognition, a service that enables you to easily and quickly integrate computer vision features directly into your own applications. At its core, Amazon Rekognition provides an API that you submit images a...

5 labs

Learn how to implement object detection on every new image uploaded on Amazon S3.

6 courses

In this Amazon Lex course you will be guided through an in-depth study of the Amazon Lex service. We review where and when to use this service to best effect. We'll go over Chatbots in general and why they have become both useful and popular. You will be in...

7 courses

This course provides a quick review and summary for what was learnt during the "Applying Machine Learning and AI services on AWS” Learning Path.  

8 exam-filled

Exam: Applying Machine Learning and AI Services on AWS

About the Author

Students7679
Labs21
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.