Are you struggling to keep your business emails organized? This course will teach you how to create and structure labels that capture the information you need to efficiently manage your inbox. From prioritizing messages to identifying urgent tasks, structuring labels and configuring entities will help you stay on top of your email game. 

About the Taxonomy Design course 

This course is meant to provide technical audiences and business users with an understanding of how to build your taxonomy before beginning model training.  

This includes creating and structuring labels, what they should capture, and how to turn specific objectives into labels.  

This course also covers defining the entity types and configurations you want to train if planning to explore and implement automation.  

The Taxonomy Design course takes 30 minutes to complete. At the end, you’ll receive a diploma of completion. 

Course prerequisites 

To enjoy this learning experience, we recommend you going through the following courses: 

• UiPath Communications Mining Overview 

• Fundamentals of Model Training 

Course audience 

The Taxonomy Design course is aimed at technical audiences and business users, as well as anybody else curious to see the power of Natural Language Processing in business. 

The Taxonomy Design course agenda 

The full agenda covers:  

• Taxonomy Design: Labels 

• Building your label taxonomy 

• Taxonomy design: Entities 

• Practice: Draft a Taxonomy of Labels and Entities 

Taxonomy Design course learning objectives 

At the end of the Taxonomy Design course, you should be able to: 

• Define what a Communications Mining taxonomy is. 

• Describe how to turn objectives into labels. 

• Identify what kinds of labels can make up a taxonomy, and what they can help to achieve. 

• List out the best practices for structuring a taxonomy. 

• Build your own taxonomy and populate a template ready to be imported into the platform. 

• Describe the different entity types. 

• Describe how to configure entities. 

• Explain 'base' entities and entities that normalize extracted values.