MLOps Essentials: Model Deployment and Monitoring Preview

MLOps Essentials: Model Deployment and Monitoring

With Kumaran Ponnambalam Liked by 248 users
Duration: 1h 23m Skill level: Intermediate Released: 10/7/2022

Course details

Suggested Prerequisites

Machine learning operations (MLOps) is one of the fastest growing subfields of artificial intelligence. In this course, instructor Kumaran Ponnambalam shows you how to deploy and monitor ML models to create structured, improved outcomes in your everyday workflow.

Learn how to implement MLOps to:

  • Create smooth upgrades of models in production on your next machine learning project.
  • Ensure continuous delivery with deployment pipelines, rollout strategies, infrastructure, and best practices.
  • Pattern, scale, build resilience, optimize, and utilize automation management tools for model serving.
  • Use monitoring pipelines, observability, metrics, production data, alerts, and thresholds for continuous monitoring.
  • Manage concept drift and feature drift, retraining models when necessary.
  • Practice effective, fair, explainable, secure, and responsible artificial intelligence.

Skills you’ll gain

Earn a sharable certificate

Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.

Sample certificate

Certificate of Completion

  • Showcase on your LinkedIn profile under “Licenses and Certificate” section

  • Download or print out as PDF to share with others

  • Share as image online to demonstrate your skill

Meet the instructor

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Contents

What’s included

  • Practice while you learn 1 exercise file
  • Test your knowledge 6 quizzes
  • Learn on the go Access on tablet and phone
  • Stay up to date Continuing Education Units

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