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.
This learning path is suited to anyone interested in applying AWS Machine Learning and Artificial Intelligence platform and application services.
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.
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.
This learning path 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 firstname.lastname@example.org
Learning Path Steps
Introduction to Applying Machine Learning and AI services on AWS Learning Path
Develop, visualize, serve, and consume a TensorFlow machine learning model using the Amazon Deep Learning AMI in this Lab.
Learn how to implement object detection on every new image uploaded on Amazon S3.
Review for Applying Machine Learning and AI services on AWS Learning Path
Exam: Applying Machine Learning and AI Services on AWS
About the Author
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.