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Welcome
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How to succeed with this course
- Match entities using Python SDK
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Why Python SDK for entity matching
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Check your knowledge
- Access and setup
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Notebook setup
- Supervised entity matching with Python SDK
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Demonstration on supervised entity matching
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Check your knowledge
- Unsupervised entity matching with Python SDK
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Demonstration on performing unsupervised entity matching
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Check your knowledge
- End of course
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Tips and tricks
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Key takeaways
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Share your feedback
Entity Matching with Python SDK
Course 3 of 7 in Data Engineer Basics - Transform and Contextualize
Learn about matching entities using Python SDK, different entity matching models, and more
In this course, you will see a demonstration of how to perform entity matching using Cognite's Python SDK, explore the available capabilities, and explain the parameter combinations suitable for the process. Additionally, you will gain a brief understanding of what happens in the backend.
This course is for data engineers looking to up their knowledge and skills in entity matching.
NOTE: This course is for the asset-centric data model. A new course for data modelling will be available in 2026.
At the end of the course, you will be able to:
- Understand why you should use the Python SDK for entity matching
- Describe when and how to use supervised and unsupervised entity matching models
- Describe different feature types and how to use them
It's recommended to have completed Cognite Data Fusion Fundamentals and Entity Matching: The Concept before taking this course, so you have a basic understanding of the CDF data model and match entities in CDF.
This course was developed by Cognite Academy, with subject matter experts:
Torbjørn Opheim | Software Engineer
Sofie Haug | Academy Engineer