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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.

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1
Theory
MLOps Concepts

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

2 hours

Folkert Stijnman Headshot

Folkert Stijnman

ML Engineer

Track statement of accomplishment
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