MLOps Engineering on AWS (MLOE)

 

Course Overview

This course builds upon and extends the DevOps methodology prevalent in software development to build, train, and deploy machine learning (ML) models. The course is based on the four-level MLOPs maturity framework. The course focuses on the first three levels, including the initial, repeatable, and reliable levels. The course stresses the importance of data, model, and code to successful ML deployments. It demonstrates the use of tools, automation, processes, and teamwork in addressing the challenges associated with handoffs between data engineers, data scientists, software developers, and operations. The course also discusses the use of tools and processes to monitor and take action when the model prediction in production drifts from agreed-upon key performance indicators.

Who should attend

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

Prerequisites

We recommend that attendees of this course have

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Course Objectives

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

ceny & Delivery methods

Szkolenie online
Modality: L

Trwa 3 dni

Cena
  • Polska: 5.200,– PLN
Classroom training
Modality: C

Trwa 3 dni

Cena
  • Polska: 5.200,– PLN

harmonogram

Polish

Strefa czasowa: Central European Summer Time (CEST)   ±1 Godzinę

Szkolenie online Strefa czasowa: Central European Summer Time (CEST)

Angielski

Strefa czasowa: Central European Summer Time (CEST)   ±1 Godzinę

Szkolenie online Strefa czasowa: British Summer Time (BST)
Szkolenie online Strefa czasowa: Greenwich Mean Time (GMT)

2 hours difference

Szkolenie online This is a FLEX course. Strefa czasowa: Gulf Standard Time (GST)
Szkolenie online Strefa czasowa: Gulf Standard Time (GST) gwarantowane!

3 hours difference

Szkolenie online This is a FLEX course. Strefa czasowa: Gulf Standard Time (GST)

6 hours difference

Szkolenie online Strefa czasowa: UTC+8
Szkolenie online Strefa czasowa: UTC+8
Data gwarantowana:   Fast Lane uruchamia wszystkie szkolenia oznaczone jako gwarantowane bez względu na liczbę uczestników. Wyjątek stanowią działania siły wyższej lub innych nieoczekiwane zdarzenia, takie jak np. wypadek lub choroba trenera, które uniemożliwią przeprowadzenie kursu.
Szkolenie Zdalne:   To jest kurs zdalny prowadzony przez instruktora
To jest kurs FLEX, który jest prowadzony zarówno wirtualnie, jak i stacjonarnie.

Europa

Niemcy

Berlin This is a FLEX course.   Strefa czasowa: Europe/Berlin Enroll:
for online training
for classroom training
Hamburg This is a FLEX course.   Strefa czasowa: Europe/Berlin Enroll:
for online training
for classroom training
To jest kurs FLEX, który jest prowadzony zarówno wirtualnie, jak i stacjonarnie.