Applying Machine Learning and AI Services on AWS

DifficultyIntermediate
AVG Duration5h
Students1099
Ratings
4.5/5
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Content
512

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 Rekognition 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
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Training Content

1
Course - Beginner - 3m
Introduction to Applying Machine Learning and AI services on AWS Learning Path
This course provides a quick introduction to the "Applying Machine Learning and AI services on AWS” Learning Path.
2
Course - Intermediate - 1h 26m
Working with Distributed Machine Learning
This course covers Distributed Machine Learning, Apache Spark, Amazon Elastic Map Reduce, Spark MLib, and AWS Glue.
3
Hands-on Lab - Intermediate - 1h 40m
TensorFlow Machine Learning on the Amazon Deep Learning AMI
Develop, visualize, serve, and consume a TensorFlow machine learning model using the Amazon Deep Learning AMI in this Lab.
4
Course - Beginner - 1h 11m
Introduction to Amazon Rekognition
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.
5
Hands-on Lab - Beginner - 1h
Automate Image Labeling with Amazon Rekognition
Learn how to implement object detection on every new image uploaded on Amazon S3.
6
Course - Intermediate - 49m
Working with Amazon Lex - Chatbots
In this course, you'll learn about the key features and components of Amazon Lex, and how to develop, configure, and build an end-to-end Chatbot using the Lex service.
7
Course - Beginner - 2m
Review for Applying Machine Learning and AI services on AWS Learning Path
This course provides a quick review and summary of what was learned during the "Applying Machine Learning and AI services on AWS” Learning Path.
8
Exam - 30m
Final Exam: Applying Machine Learning and AI Services on AWS
Final Exam: Applying Machine Learning and AI Services on AWS
About the Author
Students62655
Labs44
Courses104
Learning paths48

Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.

He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, GCP, Azure), Security, Kubernetes, and Machine Learning.

Jeremy holds professional certifications for AWS, GCP, and Kubernetes.