MLOps Engineering on AWS

This course builds on and extends the DevOps methodology used in software development to build, train and deploy machine learning (ML) models. In this three days course you will learn about the four-level MLOps maturity framework. It outlines the importance of data, model and code to successful ML deployments. We recommend you to have completed AWS Technical Essentials, DevOps Engineering on AWS and Practical Data Science with Amazon SageMaker. You will be able to prepare for the AWS Certified Machine Learning certification
AWS Partner

45,000

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What You'll learn

In this course, you will learn to:

  • 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 environments for MLOps with Amazon SageMaker
  • Explain best practices for versioning and maintaining the integrity of ML model assets (data, model, and code)
  • Describe three options for creating a full CI/CD pipeline in an ML context
  • Recall best practices for implementing automated packaging, testing and deployment. (Data/model/code)
  • Demonstrate how to monitor ML based solutions
  • Demonstrate how to automate an ML solution that tests, packages, and deploys a model in an automated fashion; detects performance degradation; and re-trains the model on top of
    newly acquired data

WHAT EXPERIENCE YOU'LL NEED

We recommend that attendees of this course have:

  • AWS Technical Essentials (classroom or digital)
  • DevOps Engineering on AWS, or equivalent experience
  • Practical Data Science with Amazon SageMaker, or equivalent experience

Who should take this course

This course is intended for:

  • 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

cLASS dELIVERABLES

• Amazon Authorised Instructors
• Official AWS Content
• Hands-on labs *(if available)
• Class completion certificates
• Exam Prep sessions

dOWNLOAD THE FULL COURSE OUTLINE

Class Completion Certificate

certificate

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FAQs

Quick answers to popular questions

To enroll in this course, choose the starting date and make an online payment. Once your payment is confirmed, our team will reach out to you.

Wire Transfer, Credit Card, Debit Card, UPI & Purchase Order.

There is no minimum number of candidates required, we are happy to train 1 to 1 . With regards to the maximum number, we can accomodate 30 learners in one batch.

  1. Training Delivered by an Amazon Authorized Instructor.
  2. AWS Content E-Kit
  3. Hands-on-labs for 30 days
  4. Class attendance certificate

You will get the access to course content & lab on first day of your training session.

The course Completion Certificate will be issued to your email id within 2 weeks of completing your course.

A one-day course could be delivered over two half day sessions (4 hours a day), or a three-day course could be delivered over five days (4 hours a day)

To enroll in this course, choose the starting date and make an online payment. Once your payment is confirmed, our team will reach out to you.

Wire Transfer, Credit Card, Debit Card, UPI & Purchase Order.

There is no minimum number of candidates required, we are happy to train 1 to 1 . With regards to the maximum number, we can accomodate 30 learners in one batch.

  1. Training Delivered by an Amazon Authorized Instructor.
  2. AWS Content E-Kit
  3. Hands-on-labs for 30 days
  4. Class attendance certificate

You will get the access to course content & lab on first day of your training session.

The course Completion Certificate will be issued to your email id within 2 weeks of completing your course.

A one-day course could be delivered over two half day sessions (4 hours a day), or a three-day course could be delivered over five days (4 hours a day)

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