Chatbot Building: Rasa, DialogFlow & WIT.AI Bots with Python
2.8 (81 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
436 students enrolled

Chatbot Building: Rasa, DialogFlow & WIT.AI Bots with Python

Rasa NLU, Rasa Core, Google DialogFlow, Facebook's WIT.AI Talking Chatbot. Rasa Facebook Massenger Chatbot. Build a Bot.
2.8 (81 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
436 students enrolled
Last updated 5/2019
English
English
Current price: $44.99 Original price: $64.99 Discount: 31% off
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This course includes
  • 4.5 hours on-demand video
  • 4 articles
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Understanding concepts of building chatbots with Rasa NLU, Rasa Core, DialogFlaw & Wit•ai
  • Building chatbots for Facebook Messenger
  • Buiding a chatbot that answers FAQs
  • Deploying your chatbot in Heroku application platform
Course content
Expand all 29 lectures 04:35:33
+ DialogFlow Python Chatbot
7 lectures 01:03:58
Entities for DialogFlow Chatbot
06:37
Webhooks with Python Flask for DialogFlow Chatbot
14:22
Contexts for DialogFlow Chatbot
16:11
Input Contexts for DialogFlow Chatbot
10:37
Chatbot Deployment on Heroku
05:30

Download the final code files of the DialogFlow chatbot.

Code Files: Final DialogFlow Python Chatbot
00:06
+ Wit.ai Python Chatbot
7 lectures 53:27
Wit.ai Intent and Entities Overview
02:25
Creating Examples Highlighting Entities for Wit.ai Chatbot
07:09
Creating a Webhook for Facebook Messenger Chatbot
08:45
Parsing Intents and Entities with Python for Wit.ai Chatbot
13:05
Currency Conversion Wit.ai Chatbot
10:33
Python Chatbot Deployment to Heroku
11:24

Download the final code files of the Wit.ai chatbot.

Code Files: Final Wit.ai Python Chatbot
00:06
+ Rasa NLU Python Chatbot
8 lectures 01:13:00
Rasa Installation and Setup
07:14
Rasa - Preparing Training Data & Training Model
16:06
Rasa Interpretation Webhook Setup
05:19
Facebook Application Setup
11:45
Facebook Echo Setup
06:38
Rasa - Interpreting Intents & Entities
15:41
Rasa - Currency Conversion Chatbot
10:11

Download the final code files of the Rasa NLU chatbot.

Code Files: Final Rasa NLU Chatbot
00:06
+ Rasa Core Python Chatbot - FAQs Chatbot
7 lectures 01:25:06
Rasa Core Overview
04:27
Rasa Getting Started
16:10
Rasa - Preparing Training Data
11:25
Facebook Application Setup
11:57
Adding More Questions & Rasa Chatbot Testing
19:38
Deployment to Heroku
21:23

Download the final code files of the Rasa Core chatbot.

Code Files: Final Rasa Core Chatbot
00:06
Requirements
  • Its necessary to have basic programming knowledge of Python
Description

Do you want to create a talking chatbot that interact with your visitors? In this tutorial, you will learn how to create Python chatbots using DialogFlow and Wit.AI platforms as well as powerful Rasa NLU and Rasa Core. DialogFlow, Wit.AI and Rasa provide several Natural Language Processing functions that parse user input and match them to the right response. Implementing NLP in your bot can be pretty difficult, but these platforms make it much easier to create a Facebook Messenger bot or a website chatbot.


DialogFlow (formerly Api.AI, Speaktoit) is a Google developer of human–computer interaction technologies based on natural language conversations. Dialogflow runs on Google Cloud Platform. In the DialogFlow Python tutorial, you will learn how to build a Facebook Messenger chatbot that incorporates NLP with Dialogflow and deploy it to Facebook.


Wit.AI makes it easy for developers to build Python chatbot applications and devices that you can talk or text to. Wit.AI is a natural language processing (NLP) tool that helps developers get structured data from chat or voice. Wit.AI makes it easy to build NLP into your chat bot, that learns from every interaction. If you want to build a Facebook bot even if you have not before, Wit.AI would be a great option. In the Wit.AI Python tutorial, you will learn how to train a Python chatbot using wit.AI by creating intents and entities for your chatbot data to build a Facebook Messenger chatbot.


Rasa is a powerful open source machine learning framework for developers to create contextual chatbots and expand bots beyond answering simple questions. In this course, you will study both Rasa NLU and Rasa Core.


  • Rasa NLU is an open-source natural language processing tool for intent classification and entity extraction in chatbots. You can think of it as a set of high level APIs for building your own language parser using existing NLP and ML libraries. he main reasons for using open source NLU are that: 1) you don’t have to hand over all your chatbot training data to Google, Microsoft, Amazon, or Facebook; 2) Machine Learning is not one-size-fits all. You can tweak and customize Python chatbot models for your training data; and 3) Rasa NLU runs wherever you want, so you don’t have to make an extra network request for every chatbot message that comes in.


  • Rasa Core leverages developers’ existing domain knowledge to help them bootstrap from zero training data, and adopts the interactive learning approach. With Rasa Core, you manually specify all of the things your bot can say and do. We call these actions. One action might be to greet the user, another might be to call an API, or query a database. Then you train a probabilistic model to predict which action your Python chatbot should take given the history of a chatbot conversation.


This Python chatbot course will help you:

  • Build chatbots with Python using Rasa NLU & Rasa Core, DialogFlow and Wit.AI

  • Use DialogFlow to build a Facebook Messenger chatbot.

  • Use Wit.AI to build a Facebook Messenger chatbot.

  • Use Rasa NLU to build a chatbot.

  • Use Rasa Core to build a chatbot.

  • Understand intents and entities.

  • Build a Facebook Messenger bot.

  • Deploy chatbots to cloud platforms such as Heroku.



Keywords: Python chatbot, google apis client, google api client, google apis, google api, google cloud platform, cloud, google dialogflow, dialogflow chatbot, Dialogflow API, chatobots, Rasa NLU, Rasa Core, Facebook Messenger chatbot.



Who this course is for:
  • Software Python developers looking to build chatbots for their websites and mobile apps
  • Developers of Facebook looking to build Massenger chatbots
  • Development professionals and students looking to learn how to use Rasa NLU, Rasa Core, DialogFlow and Wit-AI to build chatbots.