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Building Chatbots with Google Dialogflow

Up to 6h 2m
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This practical course provides an intro to the Dialogflow service and will get you up and running with building your own chatbots. We'll take an introductory look at what the Google Dialogflow tool is used for and look at the basic steps and components required to make a chatbot. We'll also discuss the use of databases and other knowledge sources in order to provide meaningful responses that give you the option to serve real-world information to your user. 

We'll walk you through an example of building an online banking customer service chatbot using Dialogflow and then you'll have the chance to build your own one thanks to our hands-on labs!

You'll also build a weather forecasting chatbot and an FAQ service, which will further enhance your knowledge of the Dialogflow service. By the end of this course, you'll have a strong foundation for working with Dialogflow.

Learning Objectives

  • Understand the fundamentals of creating chatbots using Dialogflow and how they interact with users
  • Understand the technical aspects of developing a Dialogflow application
  • Understand the user interfaces available with Dialogflow
  • Learn how to use the Knowledge service to build chatbots quickly and with less configuration
  • Get a practical understanding of how to build a chatbot with Dialogflow for a variety of uses

Intended Audience

  • Machine learning engineers
  • Anyone interested in building chatbots with Dialogflow


To get the most out of this course, you should have at least a basic understanding of:

  • Computer science techniques
  • REST APIs and SQL
  • Google Cloud Platform
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Calculated Systems
This content is developed in partnership with Calculated Systems
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About the Author

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Calculated Systems was founded by experts in Hadoop, Google Cloud and AWS. Calculated Systems enables code-free capture, mapping and transformation of data in the cloud based on Apache NiFi, an open source project originally developed within the NSA. Calculated Systems accelerates time to market for new innovations while maintaining data integrity.  With cloud automation tools, deep industry expertise, and experience productionalizing workloads development cycles are cut down to a fraction of their normal time. The ability to quickly develop large scale data ingestion and processing  decreases the risk companies face in long development cycles. Calculated Systems is one of the industry leaders in Big Data transformation and education of these complex technologies.

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