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IBM

Building AI Applications with Watson APIs

IBM via Coursera

Overview

A learner will be able to write an application that leverages multiple Watson AI services (Discovery, Speech to Text, Assistant, and Text to Speech). By the end of the course, they’ll learn best practices of combining Watson services, and how they can build interactive information retrieval systems with Discovery + Assistant.

Syllabus

  • Module 1: Introduction
    • In this module, we'll discuss the course prerequisites, scope, and the technologies that we'll be using. We'll also get you set up for using key Watson services on the IBM Cloud.
  • Module 2: Watson Discovery
    • In this module, you'll learn about Watson Discovery, a great tool to extract insight from large volumes of unstructured data. You'll also learn about how integration between Watson Assistant and Discovery works in principle.
  • Module 3: Building the Chatbot
    • In this module, we'll start to create a student advisor chatbot by leveraging Watson Assistant. We'll then use IBM Cloud Functions to integrate it with Watson Discovery.
  • Module 4: Giving it a Voice
    • In this module, you'll learn about the various options available to enable interaction with your chatbot via audio rather than textual means. In the labs, you'll work on integrating Watson Assistant with Watson Speech APIs.
  • Module 5: Deployment
    • This module will teach you how to deploy your chatbot to various channels, including Facebook Messenger and Slack.
  • Module 6: Project
    • In module 6, you'll put it all together, by using your newfound skills for the creation of a Coursera Student Advisor. This chatbot will leverage at least two Watson services, including Watson Assistant and Watson Discovery.

Taught by

Antonio Cangiano and Tanmay Bakshi

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