MLOps 101: Getting Started With ML At Scale

A year since its release, Google’s Vertex AI has not only been named a leader in AI Infrastructure but has also consistently added new capabilities to help teams accelerate ML model creation and deployment with MLOps.

But, getting started with a full-scale MLOps solution can be a challenge. With tooling, budget, and team capacity & capability to consider, how do you know where to begin?

In this webinar, Datatonic and Google Cloud share practical tips on designing and building your MLOps Platform using Vertex AI, detailing:

  1. How to pick the right approach for your MLOps solution
  2. How to prioritise the right components (for data validation, continuous training, model monitoring, and more) and tailor your solution to your needs
  3. How to get started on Vertex AI with Datatonic’s open-sourced MLOps Turbo Templates


  1. Tanmaiyii Rao, ML Specialist, Google Cloud
  2. Jamie Curtis, MLOps Business Lead, Datatonic
  3. Jonny Browning, Principal MLOps Engineer, Datatonic

    Do you want to know more about the best tools for your MLOps platform? Download our MLOps Tools Guide here.

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