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Applying Machine Learning and AI Services on AWS

Up to 6h 41m
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This course 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 course, you will be able to implement and experiment with Amazon Machine Learning platform and application services. 

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

Learning Objectives
By completing this course 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.

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 Course first. 

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

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

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About the Author

Jeremy Cook, opens in a new tab
Content Lead Architect
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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, Azure, GCP), Security, Kubernetes, and Machine Learning.

Jeremy holds professional certifications for AWS, Azure, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).

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