Building AI Applications with Watson APIs

Overview

Class Central Tips

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 and Creating a Chatbot

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. And, we'll start to create a student advisor chatbot by leveraging Watson Assistant.

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.

Deployment

This module will teach you how to deploy your chatbot to various channels, including Facebook Messenger and Slack.

Final Project

In this module, you'll put it all together, by using your newfound skills for the creation of a Coursera Student Advisor. This chatbot will leverage Watson service, Watson Assistant and GitHub

(Optional) Enhancing your Chatbot with Discovery

In this module, you'll learn about Watson Discovery, a paid service and 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. We'll then use IBM Cloud Functions to integrate your Chatbot with Watson Discovery.