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Course Overview

This course is designed for candidates looking to demonstrate foundational-level knowledge of machine learning (ML) and artificial intelligence (AI) concepts, and related Microsoft Azure services. You will learn how to use Azure services to create machine learning, computer vision, natural language processing, and conversational AI solutions through hands-on activities. The course is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, some general programming knowledge or experience would be beneficial.

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Key Learning Areas

  • 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
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Course Outline

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

After completing this module, you will be able to:

  • Describe Artificial Intelligence workloads and considerations

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

After completing this module, you will be able to:

  • Describe fundamental principles of machine learning on Azure

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

After completing this module, you will be able to:

  • Describe features of computer vision workloads on Azure

Natural Language Processing

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.After completing this module, you will be able to:

  • Describe features of Natural Language Processing (NLP) workloads on Azure

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

After completing this module, you will be able to:

  • Describe features of conversational AI workloads on Azure
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Who Benefits

The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don’t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful.

Exam AI-900: Microsoft Azure Data Fundamentals
Prove that you can describe the following: AI workloads and considerations; fundamental principles of machine learning on Azure; features of computer vision workloads on Azure; features of Natural Language Processing (NLP) workloads on Azure; and features of conversational AI workloads on Azure.

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Prerequisites

Familiarity with computers and using a web browser.

Want this course for your team?

Atmosera can provide this course virtually or on-site. Please reach out to discuss your requirements.

Atmosera is thrilled to announce that we have been named GitHub AI Partner of the Year.

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