AI- 900: Microsoft Azure AI Fundamentals


  • Duration: 1 Day
  • Mode of Delivery: Online -Instructor-led training
  • Level: Beginner
  • Job role: Support role for data engineering
  • Preparation for exam: AI-900
  • Cost: USD$1,250.00

This 1-day instructor-led course introduces the fundamental concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course provides a practical, hands-on approach in which you will get a chance to see AI in action and try Azure AI services for yourself.




Ideal for students who want to learn about the types of solutions AI makes possible, and the services on Microsoft Azure that you can use to create them.


  • Basic programming skills: Any language such as python, C# etc. will be okay for you to start.
  • It is also essential to know the statistical graphs such as Histogram, Scatterplot, Line Chart, etc. Calculating Probability and its related concepts such as odds and odds ratio etc

Skills Gained

After completing this course, students will be able to:
• Describe Artificial Intelligence workloads and considerations
• Describe fundamental principles of machine learning on Azure
• Describe features of computer vision workloads on Azure
• Describe features of Natural Language Processing (NLP) workloads on Azure
• Describe features of conversational AI workloads on Azure

Course outline

Module 1: Introduction to AI

In this module, you’ll learn about common uses of artificial intelligence (AI), and the different types of workloads associated with AI. You’ll then explore considerations and principles for responsible AI development.

  • Artificial Intelligence in Azure
  • Responsible AI

Module 2: Machine Learning

Machine learning is the foundation for modern AI solutions. In this module, you’ll learn about some fundamental machine learning concepts, and how to use the Azure Machine Learning service to create and publish machine learning models.

  • Introduction to Machine Learning
  • Azure Machine Learning

Module 3: Computer Vision

Computer vision is the area of AI that deals with understanding the world visually, through images, video files, and cameras. In this module you’ll explore multiple computer vision techniques and services

  • Computer Vision Concepts
  • Computer Vision in Azure

Module 4: Natural Language Processing (NLP)

This module describes scenarios for AI solutions that can process written and spoken language. You’ll learn about Azure services that can be used to build solutions that analyze text, recognize and synthesize speech, translate between languages, and interpret commands.

  • Introduction to Natural Language Processing
  • Using Natural Language Processing Services

Module 5: Conversational AI

Conversational AI enables users to engage in a dialog with an AI agent, or Bot, through communication channels such as email, webchat interfaces, social media, and others. This module describes some basic principles for working with bots and gives you an opportunity to create a bot that can respond intelligently to user questions.

  • Conversational AI Concepts
  • Conversational AI in Azure


Click on the following link to see the current Course Schedule
Our minimum class-size is 3 for this course.
If there are no scheduled dates for this course, it can be customized to suit the time and skill needs of clients and it can be held online, at a rented location or at your premises.
Click on the following link below to arrange for a custom course: Enquire about a course date

Product Information

AI is the creation of software that imitates human behaviors and capabilities. Some of these key activities include:
• Making decisions based on data and past experience
• Detecting anomalies
• Interpreting visual input
• Understanding written and spoken language
• Engaging in dialogs and conversations

The table below shows all the technologies and tools used in the course.

Azure Manage subscriptions, create workspaces, create resources, manage services.
Azure Bot Service Managed service purpose-built for bot development.
Azure Machine Learning Automated Machine Learning Manage the machine learning lifecycle.
Azure Machine Learning designer Visually connect datasets and modules on an interactive canvas to create machine learning models.
Cognitive Services Comprehensive family of AI services and cognitive APIs to help you build intelligent apps.
Computer Vision An AI service that analyzes content in images.
Custom Vision An AI service and end-to-end platform for applying computer vision to your specific scenario.
Face An AI service that analyzes faces in images.
Language Understanding (LUIS) An AI service that allows users to interact with your applications, bots, and IoT devices by using natural language.
Form Recognizer The AI-powered document extraction service that understands your forms.
Learn Provides interactive, hands-on learning paths, which contain the learning path, course modules, and lessons used in this course.
QnA Maker A cloud-based API service that lets you create a conversational question-and-answer layer over your existing data.
Speech Speech-to-Text, Speech Translation, and Text-to-Speech service feature that translates speech in real time.
Text Analytics An AI service that uncovers insights such as sentiment, entities, and key phrases in unstructured text.
Text-to-Speech A Speech service feature that converts text to lifelike speech.
Translator Text An AI service for real-time text translation.
Visual Studio Codespaces Cloud-hosted dev environments accessible from anywhere.

Additional Information

CANCELLATION POLICY – There is never a fee for cancelling seven business days before a class for any reason. Data Vision Systems reserves the right to cancel any course due to insufficient registration or other extenuating circumstances. Participants will be advised prior to doing so.


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