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IBM: Smarter Chatbots with Node-RED and Watson AI

Learn how to use Node-RED to augment the capabilities of your Watson Assistant chatbots by integrating services such as Watson Translate and Text to Speech. You'll also practice deployment of chatbots to Facebook Messenger.
Smarter Chatbots with Node-RED and Watson AI
3 semanas
2–4 horas por semana
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Sobre este curso

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In this course, you'll learn how to use Node-RED to augment the capabilities of your Watson Assistant chatbots by integrating them with services such as Watson Translate and Text to Speech. You'll also practice deployment of chatbots to Facebook Messenger.

Node-RED, which is built on Node.js, is a browser-based flow editor that makes it easy to wire together devices, APIs, and online services by simply dragging and dropping nodes on a palette. You then connect, or wire, the nodes to create flows that can be then deployed to the lightweight Node.js runtime with a single click.

Get hands-on experience in this course as you learn how to use Node-RED to augment the capabilities of your Watson Assistant chatbots. You will learn how to:
  • Convert speech to text
  • Analyze tone
  • Translate text into different languages
  • Send tweets through Twitter
  • Add audio and video capabilities
  • Set up a chatbot using the IBM Watson Assistant service and Facebook Messenger.
This course requires no programming experience!

De un vistazo

  • Institution IBM
  • Subject Informática
  • Level Intermediate
  • Prerequisites
    • You will work with basic HTML and JavaScript, but the course labs will provide that code.
    • If you are not familiar with Watson Assistant, you should take the How to Build Chatbots and Make Money course first.
  • Language English
  • Video Transcript English
  • Associated skillsNodes (Networking), Speech Synthesis, Chatbot, Application Programming Interface (API), Artificial Intelligence, Node-RED, Online Service Provider, Node.js

Lo que aprenderás

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  • Create a Node-RED application
  • Consume web services from Node-RED
  • Integrate Watson Assistant with other Watson services
  • Connect your Node-RED applications to external services like Twitter
  • Deploy your chatbots to Facebook Messenger

Plan de estudios

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Get started

  • Learning objectives
  • Prerequisites
  • Grading scheme
A business opportunity

  • Make money with chatbots
Lab 1: Create your first Node-RED flow

  • Lab 1 overview
  • 1. Create a Node-RED instance
  • 2. Connect Watson services
  • 3. Create your first flows
  • Lab 1 solution
  • Review questions

Lab 2: Build a web page and create a REST API in Node-RED

  • Lab 2 introduction
  • 1. Create a simple web page
  • 2. Add JavaScript to your web application
  • 3. Create a REST API
  • 4. Consume the Watson Translator service
  • Lab 2 solution
  • Review questions

Lab 3: Translate text, analyze tone, add audio, and send tweets from your Node-RED application

  • Lab 3 introduction
  • 1. Find community nodes
  • 2. Add the community nodes to the Node-RED palette
  • 3. Add the Speech to Text, Tone Analyzer, and Text to Speech services
  • 4. Re-create the Interpreter application
  • 5. Prepare for the OK Watson application
  • 6. Add link nodes to more easily view the logic of the application flow
  • 7. Import the OK Watson flow
  • 8. Connect to your Twitter account
  • 9. Add the community nodes to the package.json file (alternative method)
  • Lab 3 summary
  • Lab 3 solution
  • Review question

Lab 4: Create cognitive web pages and a Messenger bot

  • Lab 4 overview
  • 1. Obtain Facebook Messenger credentials
  • 2. Create Node-RED webhooks
  • 3. Create the Node-RED Messenger listener
  • 4. Create a Node-RED Messenger writer
  • 5. Build a video captioning application
  • Lab 4 solution
  • Review question

Lab 5: Build HTML web pages that use Git repositories that can reuse browser-side JavaScript

  • Lab 5 introduction
  • 1. Connect the Watson Conversation service to the Messenger bot
  • 2. Build a Node-RED application that can reuse CSS and browser-side JavaScript
  • Lab 5 Solution
  • Review question

Final Exam

Summary

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