Model Operationalization

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  • Mar 21-22
     March 21, 2023 - March 22, 2023
     9:00 am - 5:00 pm
  • Nov 28-29
     November 28, 2023 - November 29, 2023
     9:00 am - 5:00 pm
  • Jul 4-5
     July 4, 2023 - July 5, 2023
     9:00 am - 5:00 pm

Model Operationalization

About the course

Are you struggling to operationalize your models or achieve the success from AI you envisioned? Without model operationalization, you won’t make any impact on the business process because business users cannot access your model output. This module is designed as a step-by-step guide to explain all the ‘need to knows’ and structure to model operationalization. We begin by outlining the complete process of model operationalization, followed by a deep dive into model deployment. Then we discuss APIs in general, REST APIs and how to put you model behind an API. Furthermore, we’ll cover how to use your model behind an API in a web application, and how to orchestrate the entire process.


Why this is for you

Without putting your model in production, you are actually not making any impact on the business, because business users cannot change their processes or decisions based on your model output. As a Data Scientist or Engineer, you are responsible for making sure that your model is operationalized properly. This training is designed to show you how!


For whom

This training is for Data Engineers, AI Engineers, and Data Scientists who want to make a real impact with their models by putting them in production. This training contains a substantial amount of case work in Python, so prior knowledge of Python is required. This means that basic concepts like functions, loops and dictionaries should be familiar.


What you’ll learn

  1. Model operationalization
  2. Model deployment
  3. APIs, REST APIs, and how they work in relation to analytical web applications
  4. Model deployment behind APIs
  5. Orchestration basics using Jenkins

Learning Goals

  • Model operationalization basics – Get an overview of the process and the technology options
  • Model deployment – Explain the role of model deployment and the different types of deployment methods
  • Working with APIs – Learn what an API is, how to define them and implement one yourself
  • Model deployment behind APIs – Learn how to deploy your model behind an API and how it can be called from a web application
  • Orchestration basics using Jenkins – Use Jenkins as an orchestrator to call your model and all other operationalization steps

Theory and practical use

All trainings in the GAIn portfolio combine high-quality standardized training material with theory sessions from experts and hands-on experience where you directly apply the material to real-life cases. Each training is developed by top of the field practitioners which means they are full of industry examples along with practical challenges and know-how, fueling the interactive discussions during training. We believe this multi-level approach creates the ideal learning environment for participants to thrive.