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MLOps Fundamentals

Dive into the foundations of Machine Learning Operations (MLOps), learning the concepts of productionizing and monitoring machine learning models!
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TheoryMachine Learning14 hours6,200

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Track Description

MLOps Fundamentals

Dive into the foundations of Machine Learning Operations (MLOps), learning the core concepts of productionizing and monitoring machine learning models to add business value! This skill track covers the complete life-cycle of a machine learning application, ranging from the gathering of business requirements to the design, development, deployment, operation, and maintenance stages. This track includes conceptual courses designed to help you expand your data science knowledge into the world of production machine learning software! Upon completion of the track, you'll be equipped with an MLOps mindset and will be deeply familiar with concepts such as CI/CD and CM/CT, experiment tracking, model registries, feature stores, and different deployment strategies. Additionally, you'll gain an understanding of critical elements of operating machine learning applications in production, such as data drift and model drift.

Prerequisites

There are no prerequisites for this track
  • Course

    1

    MLOps Concepts

    Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.

  • Course

    In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

  • Course

    Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

MLOps Fundamentals
4 courses
Track
Complete

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