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MLOps Engineering on AWS

Productionize ML models using repeatable and reliable workflows with MLOps Engineering on AWS

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MLOps Engineering on AWS

Could your Machine Learning (ML) workflow use some DevOps agility? MLOps Engineering on AWS will help you bring DevOps-style practices into the building, training, and deployment of ML models by learning from an expert AWS instructor.

In this 3-day, course you will learn how to address the challenges associated with hand-offs between data engineers, data scientists, software developers, and operations through the use of tools, automation, processes, and teamwork. By the end of the course, go from learning to doing by building and troubleshooting an ML pipeline.

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Course details

  • Level: Intermediate
  • Type: Classroom (virtual and in person)
  • Length: 3 days
  • Explain the benefits of MLOps
  • Compare and contrast DevOps and MLOps
  • Evaluate the security and governance requirements for an ML use case and describe possible solutions and mitigation strategies
  • Set up experimentation for MLOps with Amazon SageMaker
  • And much more
  • MLOps engineers who want to productionize and monitor ML models in the AWS cloud
  • DevOps engineers who will be responsible for successfully deploying and maintaining ML models in production

Required:

This course is offered in English.