Machine Learning Operations

Introduction

This course teaches you how to develop scalable, maintainable, and efficient machine learning algorithms using object-oriented programming in Python. Specifically, it focuses on data engineering, model development, model registry, deployment, and monitoring. From a business perspective, the course covers the process of transitioning models from the experimental stage to production environments, with a focus on the entire lifecycle of the model.

Course content

• Basic object oriented programming concepts, e.g., classes, constructors and methods
• Further topics in object-oriented programming, such as inheritance, overriding and polymorphism
• Version control with Git and GitHub
• Data engineering and data curation and preprocessing
• Model lifecycle:
  • development 
  • training
  • registry
  • deployment
  • monitoring

Disclaimer

This is an excerpt from the complete course description for the course. If you are an active student at BI, you can find the complete course descriptions with information on eg. learning goals, learning process, curriculum and exam at portal.bi.no. We reserve the right to make changes to this description.