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
- Domains of Artificial Intelligence
- History, Current State and Future
Bots and UX
Bots are the future! They are 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
Here, you will learn how to create a simple bot, and debug it with the Bot Emulator.
- The Microsoft Bot Framework
- Debugging your bot with the bot Emulator
- Turns, Messages and Activities
- Conversations and Channels
As your bot grows, you need to organize your code, this is where dialogs come in.
- Waterfalls and Prompts
- Composing Dialogs
Intercept messages and take action with middleware.
- Built-in Middleware
- Custom Middleware
- Activity Handlers
This module presents the theoretical background in Machine Learning required for the next modules.
- Supervised vs Unsupervised
- Machine Learning Process
- Deep Learning
- Data Preparation
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
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
Azure 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.
- Working with Datasets
- Data Preparation
- Exploring modelling techniques
- Training and evaluating models
- Exposing the model as a webservice
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
- Setting up Search Indexing
- Filtering, Sorting, Facets, ...
- Query Syntax
- Consuming 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
- Connect your bot to Skype, Slack, Facebook, ...
- Bot Analytics
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.