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.
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.