With all the options out there, creating a voice and chatbot today can be a daunting decision. In this course, you'll take the stress out of figuring it all out by learning how to build a cross-channel conversational bot that works everywhere.
Do you know how to build a chatbot or a voice interface? Amazon Echo or Google Home? Facebook Messenger or Slack bot? How about all of the above and more? In this course, Creating Voice and Chatbots That Work Everywhere, you'll learn how to build a single conversational interface in C# and the .NET Web API framework that works across all chat and voice channels from Amazon Alexa, Google Assistant, Microsoft Cortana, Slack, Facebook Messenger, SMS, and many others. First, you'll explore the overall landscape and conversational flow design concepts. Next, you'll dive into intents and intent handling. Finally, you'll discover advanced debugging techniques using Remote Debugger. When you're finished with this course, you'll not only have a clear understanding of how you can deploy bots across multiple voice and chat channels, but you'll also have a fully functional bot prototype that you can continue to grow and evolve.
Walter Quesada is a Software Engineer and Experience Technologist with over 20 years architecting and developing solutions for SMB's to Fortune 500 companies. Although primarily focused on architecting and programming .NET/C# applications, he enjoys some C++, Objective-C, Python, node.js, and Java fun from time to time.
Course Overview Hello, I'm Walter Quesada, and welcome to my course, Creating Voice and Chatbots That Work Everywhere. As an Amazon Alexa champion and a conversational interfaces advocate, I'm here to show you how to create a single bot that works across multiple channels seamlessly. Let's face it, voice and chatbots are everywhere these days from Amazon Alexa, Google Assistant, Microsoft Cortana, to chatbots on Slack, Facebook Messenger, and even on SMS. In this course, we're going to design and build a bot in C# and a. NET Web API framework, and you won't even need any natural language understanding or artificial intelligence experience to pull it off. Some of the major topics that we will cover include conversational interface design, creating Amazon Alexa Skills, the Microsoft Bot Framework, API. AI integrations, now called Dialogflow, as well as some advanced debugging techniques via Remote Debugger. By the end of this course, you will not only have a clear understanding of how to deploy a bot across multiple voice and chat channels, but you will also have a fully functional bot prototype that you can continue to grow and evolve. So I hope you will join me on this incredible journey to learn all about conversational interfaces with the Creating Voice and Chatbots That Work Everywhere course, at Pluralsight.
Making Cross-channel Support a Breeze Hello, I'm Walter Quesada, and welcome to another module in the Creating Voice and Chatbots That Work Everywhere course. In this module, we're going to quickly cover the cross-channel architecture of our new bot. We'll then take a deep look at the request and response formats for Alexa, API. AI, and the Bot Framework to see if we can identify the overlaps, as well as any unique properties we'd need to consider when drafting our common model. After that, we should have a pretty clear understanding of the what and the how we're going to build our new multi-channel bot. So with that in mind, we'll start to get our hands dirty by creating a new Visual Studio solution and core projects, then dive into creating a common conversational model that supports all the channels and natural language understanding services we've scoped for so far, such as Alexa, Google Assistant, Cortana, Facebook Messenger, Slack, Twilio, and API. AI.
Kicking Off the Conversation with the .NET Web API Framework Hello, I'm Walter Quesada, and welcome to another module in the Creating Voice and Chatbots That Work Everywhere course. In this module, we'll begin by writing our common model in C# that map all our endpoint service models, such as the API. AI and Alexa service models to our new common model that the rest of our workflow can work with. Part of that workflow includes an intent router, which we'll also create, that will help us route incoming intents to their respective intent handler. Speaking of intent handlers, that's right, we'll need to create those as well, specifically the welcome intent and the reservations intent that we've designed for in our conversational flow diagram and that we've already added to API. AI and Alexa. Lastly, we'll look at some runtime debugging tips and techniques using invaluable tools, such as remote debugging in Azure.
Talking to Alexa, Cortana, Google, Slack, Facebook, and Twilio Hello, I'm Walter Quesada, and welcome to the last module in the Creating Voice and Chatbots That Work Everywhere course. In this module, we're going to start to get into some advanced development techniques around dialogs, and then take Amazon Alexa's new interaction model designer out for a spin. Afterwards, we'll update our commonModel and CommonModelMappers to handle both the Alexa dialogs, as well as some of the visual elements, such as cards. Then, we'll add in a database so that we can store our Tex-Mex Tacos table reservations, as well as any other data we want to store. And lastly, we'll see our new amazing bot come to life in all the channels that we've scoped for starting with Alexa, and Google Home, Cortana, Facebook Messenger, Slack, and finally, SMS via Twilio. Also, keep in mind that API. AI had changed their name during the production of this course, so you might see the name Dialogflow appear on the screen while I mention API. AI. Just keep in mind that they're one and the same. Now I don't know about you, but I'm freaking stoked on getting my bot up and running on all these channels, so let's do this.