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Amazon Web Services (AWS)

MLOps Engineering on AWS

Bring DevOps discipline to machine learning.

3 daysIntermediate3 modulesAWS Machine Learning Engineer - Associate
Overview

About this course

Bring DevOps discipline to machine learning. You will build and automate ML pipelines, use SageMaker for experiments, tuning and deployment, set up CI/CD for models, data and code, and monitor models once they are live.

What you'll learn

What you'll learn

  • Implement DevOps best practices in machine learning workflows
  • Design, deploy, and monitor secure, scalable ML pipelines
  • Use Amazon SageMaker for experimentation, tuning, and deployment
  • Automate CI/CD workflows for ML models, data, and code
  • Take action when the model prediction drifts from KPIs
  • Extend the DevOps approach to ML teams including data scientists, data engineers, and software developers
Curriculum

Curriculum

3 modules
  • Overview of MLOps and its importance in deploying machine learning models
  • Addressing the challenges associated with ML handoffs and teamwork
  • Setting up secure environments and using Amazon SageMaker Studio
  • Data versioning and pipeline structure
  • Designing CI/CD pipelines for ML deployment
  • Automating model packaging, testing, and deployment
  • Implementing security, A/B testing, and rollback strategies
  • Real-world scenarios and best practices
  • Tools and processes to monitor and take action
  • Model drift detection, alerting, and retraining
  • Multi-account pipeline strategies
  • Troubleshooting and human-in-the-loop feedback systems
Who it's for

Who it's for

ML engineers, DevOps engineers and data scientists operating models in production.

Before you start

  • AWS Technical Essentials , or equivalent experience
  • DevOps Engineering on AWS , or equivalent experience
  • Practical Data Science with Amazon SageMaker , or equivalent experience
Certification

Prepares for

Let's plan your next step together.

Tell us the course or certification you have in mind and we'll send the outline, upcoming dates, fees and private-team options.

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