Building Intelligent Applications Training Course

Overview

Intelligent applications (aka intelligent apps and I-apps) are next generation apps that can continually learn from user interactions to provide better value and relevance to users.

In this instructor-led, live training, participants will learn how to build intelligent mobile applications and bots.

By the end of this training, participants will be able to:

  • Understand the fundamental concepts of intelligent applications
  • Learn how to use various tools for building intelligent applications
  • Build intelligent applications using Azure, Cognitive Services API, Stream Analytics, and Xamarin

Audience

  • Developers
  • Programmers
  • Hobbyists

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice

Requirements

  • Basic programming experience
  • Basic familiarity with C#

Course Outline

Introduction

Understanding What Intelligent Mobile Applications Are

Setting Up the Development Environment

Overview of Azure Machine Learning Web Services

Using the Azure Machine Learning Studio

Learning How to Publish a Web Service in Azure

Viewing Data in Microsoft Excel in Azure

Creating Sample Applications in Azure

Using Microsoft Cognitive Services and APIs

Introduction to Text Analytics

Setting Up the Text Analytics API

Working with Text Analytics

Understanding the Bot Framework

Learning Bot Basics

Building a Simple Bot

Enhancing Your Bot and Its Functionalities

Learning Real Time Event Processing

Understanding Real Time Analytics

Using Azure Stream Analytics

Integrating Machine Learning into Stream Analytics

Using Xamarin

Using Azure Search

Understanding the Benefits of an Intelligent Search-Enabled Mobile Application

Project: Building an Intelligent Search-Enabled Application for Real Estate Listings

  • Implementing Type-Ahead Search Suggestions
  • Implementing Full-Text Search and Paging of Results
  • Implementing Search Results Filters
  • Implementing the Lookup Feature
  • Using Machine Learning Techniques for Item Recommendations
  • Scoring and Tuning of Search Results

Summary and Conclusion

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