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Developing Solutions and Bots with the Microsoft AI Platform

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26 Nov 2018
14 Jan 2019
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What is Artificial Intelligence?

In this chapter you will get a short overview about what AI exactly is, and what we could do with it.

  • Definitions of artificial Intelligence
  • Problems and approaches
  • Types of artificial intelligence
  • Applications and risks

Bots and UX

Bots are the future! They allow to create applications that interact naturally with users on social media, websites, Cortana, etc. But do you design good interaction with your bot?

  • What makes a good bot?
  • What bots can and cannot do
  • Designing a dialog flow
  • Bot design guidelines
  • (Anti-)patterns

Creating Bots

Here, you will learn how to create a simple bot, and run it on various channels.

  • The Microsoft Bot Framework
  • The Bot Framework REST API
  • Creating an Echo bot
  • Running your bot in the bot emulator
  • Debugging Bots
  • Messages and activities
  • Creating Dialogs
  • Generating Dialogs with FormFlow
  • Creating Channels
  • Adding Channel-specific functionality

Azure Cognitive Services

Your intelligent app needs to understand its environment and make decisions. For that you can use pre-trained cognitive services that detect sentiment, recognize speakers, understand pictures, etc.

  • What is Cognitive services?
  • Image Classification, Recognition and moderation
  • Person Identification
  • Speech-to-text, text-to-speech
  • Speaker recognition and real-time translation
  • Visual Search
  • QnA

Natural Language Processing with LUIS

Your bots would be useless if they wouldn't understand their users. LUIS allows us to create models that will allow us to interpret what the user wants, that can be used by your bots.

  • The Language Understanding Intelligent Services (LUIS)
  • Intents, Entities and Utterances
  • Using prebuilt models
  • Entity types
  • Training and testing LUIS
  • Calling LUIS from a bot
  • Integrating LUIS with Speech
  • Comparison with Watson

Creating A.I. with Machine Learning

What if Cognitive Services is not enough? Time for creating your own Artificial Intelligence. Machine Learning allows you to "learn" from existing data, so you can make predictions for new data.

  • Why machine learning?
  • Working with datasets
  • Data Preparation
  • Exploring modelling techniques
  • Training and evaluating models
  • Exposing the model as a webservice
  • Consuming your model
  • Visual Studio Tools for AI

Exposing your content to AI with Search

If your intelligent app needs to supply useful information to your customers, it needs to be able to access and search the information you have to offer. In this chapter you will learn how to make content searchable, and how to query your content intelligently.

  • Setting up Search Indexing
  • Push vs Pull indexing
  • Relevance Tuning
  • Cognitive Search and content augmentation
  • Querying your search-service

Azure Bot Service

Let's get your bot into the cloud and on your favorite chat applications using Azure Bot Service. It will make it easier for managing your bot, connecting it to the outside world, and looking how he's doing.

  • Deploy a bot to Azure Bot Service
  • Bot Management
  • Online Code Editor and Testing
  • Bot Analytics
  • Connect your bot to Skype, Slack, Facebook, ...

This is for the developer who is not satisfied with a normal app. This is for the developer looking for the 'wow'-factor. AI is not just for the greats, it's at the fingertips of any developer without having to be a data-scientist. In this course you are taken through all relevant topics to build intelligent applications. We'll focus on building a bot, but any user interface can be made intelligent with a pinch of AI.

This course targets professional developers that want to get started with the Microsoft AI platform. Participants of this course need to have a decent understanding of .NET and preferably some experience with Microsoft Azure.

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