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Building Chatbots with Google Dialogflow: Part 1

Developed with
Calculated Systems

Contents

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Building Chatbots with Google Dialogflow
1
Introduction
PREVIEW2m 17s
2
How & Why
PREVIEW12m 18s
6

The course is part of this learning path

Building Chatbots with Google Dialogflow
2
1
4
Introduction
Overview
Difficulty
Intermediate
Duration
38m
Students
124
Ratings
5/5
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Description

This course is the first in a two-part series that explores how to create a chatbot using Google Dialogflow. 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 cover the concepts and technical aspects to consider when building a chatbot, and then put these into context by applying them to a real-world scenario.

Learning Objectives

  • Understand the fundamentals of creating chatbots using Dialogflow
  • Learn how chatbots interact with users
  • Understand the technical aspects of developing a Dialogflow application
  • Learn how the concepts covered in the course can be applied to a real-world scenario

Intended Audience

  • Anyone looking to build chatbots using Google Dialogflow

Prerequisites

In order 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
Transcript

Hello everyone and welcome to part one of a class on Google Dialogflow. In this class, we'll be diving into how to create a chat bot that utilizes natural language understanding. Over the course of this lesson, we'll be taking an introductory look at what the Google Dialogflow tool is used for, understanding the basic steps and components required to make a chatbot and look at how Dialogflow can create real-world applications quickly.

Additionally, we're going to be covering the use of databases and other knowledge sources in order to provide meaningful responses and insights to otherwise hard to access information. This first part will focus on helping you understand all of the specifics and baseline of which Dialogflow is built on, and the second part will show how to implement it.

Although most of this course is introductory level, there are a few nice to haves. A basic understanding of computer science is needed of course, as we'll be going into concepts such as variables and programming flows, but it's also helpful to understand concepts such as REST APIs and SQL.

Also, if you're somewhat familiar with Google Cloud, not detailed but the concepts, it really helps because Dialogflow leverage is serverless functions in several parts of the Google Cloud ecosystem to function. Additionally, some advanced solutions of Dialogflow may wish to leverage JavaScript in order to help build out custom functionality, but that's not entirely needed and not even referenced until part two of this class. 

In general, this is targeted for people who want to learn how to make a chat bot in a very practical sense. Although using Dialogflow, we'll be covering concepts around what general function chatbots need to accomplish and many of the concepts taught here will actually be useful in general human machine conversational tools and human language understanding.

And before we get started, a little bit about me. My name is Chris Gambino and I'm one of the co-founders and lead architects at Calculated Systems. I have a lot of experience building data systems, having previously worked at Google Cloud, and some of the projects I've been working on recently actually leveraged Dialogflow in a big data setting. Particularly, there's one in which we're helping serve e-commerce data over SMS and that combines both high volume and high complexity information. So we'll actually be using some of those lessons directly as examples in this class.

About the Author
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Calculated Systems
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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.