
This video lists goes through the topics that will be covered in this course
This topic defines a BOT and understands its significance
You will go through the design aspect of bots. What are the design considerations while creating a bot. A Bot meant for enterprise or niche industry like HR or a CRM should behave differently than a bot made to serve general public for e.g. a taxi booking bot. This lesson highlights such considerations that will help learners give a unique personality to the Bot.
This lesson creates the development environment by installing NodeJS and download Heroku CLO . I have also attached a NODEJS tutorial ebook in case you want to go through some of its concepts.
This lesson explains the skype framework and a flow diagram on we can write a skypebot using NodeJS and Microsoft Bot framework
You will learn the prerequisites needed to write a bot for Skype. This lessons installs all the prerequisite needed.
In this lesson we will write complete code for the Skype bot. Complete source code is attached for you to go through.
In this lesson, you will learn to register the bot on Microsoft development framework portal and also upload on Heroku cloud
In this lesson, we will complete the coding part and test on skype.
In this lesson, you will go through the facebook messenger architecture and how we will wire up our NodeJS code to Facebook developer portal.
In this lesson, you will learn the coding part of writing a Facebook bot. The complete source code is also attached in this lesson.
In this topic, we will build up a good case for NLP. How does NLP aid bot development. We study the shortcoming of building bots without using NLP platform by going through the code written in earlier lesson and ascertain the fact that with NLP, bot development time can be accelerated with positive benefits.
In this lesson, you will be introduced to Dialogflow and touch briefly its various components. We will also deploy a ready-made weather bot on heroku cloud and test the end to end flow to understand how Dialogflow works.
Also attached is the DialogFlow Agent under resources.
In this lesson user will understand the concept of Intents.
The Dialogflow agent that has been used to demonstrate the concept has been attached with this lesson.
In this lesson we will go through with the concept of Contexts In Dialgflow, we write a McDelivery Bot in Dialogflow – a fictitious McDonald Order taking bot which has a slightly complex flow. This bot will clearly explain how contexts can be used in conversation flows that diverge and merge later.
You can download the Dialogflow agent in this lesson
In this lesson, you will understand the Dialogflow's Fulfillment and Actions.
Next, we will write an end to end Bus Arrival Time notifier bot using Dialogflow and NodeJS. The Bus Arrival Time API is provided by Singapore's Land Transport Authority https://www.mytransport.sg/content/mytransport/home/dataMall.html) . The Bot uses the API to fetch live Bus arrival timings at a bus stop. We build this first for Facebook messenger.
Next, we will write an end to end Bus Arrival Time notifier bot using Dialogflow and NodeJS. The Bus Arrival Time API is provided by Singapore's Land Transport Authority https://www.mytransport.sg/content/mytransport/home/dataMall.html) . The Bot uses the API to fetch live Bus arrival timings at a bus stop. We build this first for Facebook messenger.
Next, we will write an end to end Bus Arrival Time notifier bot using Dialogflow and NodeJS. The Bus Arrival Time API is provided by Singapore's Land Transport Authority https://www.mytransport.sg/content/mytransport/home/dataMall.html) . The Bot uses the API to fetch live Bus arrival timings at a bus stop. We build this first for Facebook messenger.
This tutorial explains the same BusArrivalTime notifier bot but with Dialogflow V2 API
In this lesson we will continue with the same bot, however will write an chatbot with HTML and Javascript.
In this lesson we will create an Android app, that talks to the same backend created in earlier lesson that gives bus arrival time given a bus stop.
In this lesson you will learn how to use Webhook with slotfilling feature in Dialogflow. Here we will create a BOT in Dialogflow and fulfillment in NodeJS. THis example will help you understand how slotfilling can help in fetching details and filling parameters at the backend.
This tutorial explains webhook slotfilling using DialogFlow V2 API
In this lesson, you will learn how to validate user input in the fulfilment web service - We create a BOT in Dialogflow and fulfillment in NodeJS.
This tutorial explains Validations using Dialogflow V2 API
Whether you are a novice would be bot developer or have just started your journey in bot development, this course will smoothen your journey by explaining you the bot development process clearly with examples using Dialogflow and NodeJS.
This course teaches invaluable concepts of Dialogflow that are essential for creating bots for Facebook messenger, Skype, web and Android platform.
Difficult concepts in Dialogflow like Webhook slot filling, validation of user inputs during backend fulfillment, and concepts like Entities, Contexts, Actions, Events are explained with live examples in NodeJS for better clarity which otherwise are not well documented on Dialogflow.comEach topic is covered in top down fashion with practical, hands-on examples.
The later part of the course covers some advanced concepts. A real-life Bus Arrival time bot is written in Node JS using Dialogflow for Facebook messenger, as an Android app and also as a chat enabled web application. The Bus Arrival time bot chats with the user and accepts a parameter called BusStop Number and provides the user the estimated time of arrival of all the busses at that stop. The Bus Arrival Time API is provided by Singapore's Land Transport Authority. The Bot uses the API to fetch live Bus arrival timings at a bus stop. Complete source code is provided for the learners to learn how an end to end bot is created using Dialogflow and NodeJS.
UPDATE: Examples using Dialogflow V2 has been added recently. I will keep adding more examples using Dialogflow Version 2.