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    12/16/2024 12/16/2024 ICLVLTGTR Register
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    Overview

    This course introduces fundamentals 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 is designed as a blended learning experience that combines instructor-led training with online materials.

    Audience Profile

    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.

    Job role: AI Engineer

    Preparation for exam: AI-900

    Features: none

    Skills gained

    • 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

    Prerequisites

    Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services.

    Specifically:

    • Experience using computers and the internet.
    • Interest in use cases for AI applications and machine learning models.
    • A willingness to learn through hands-on exploration.

     

    Description

    Module 1: Explore Fundamentals of Artificial Intelligence

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

    Lessons

    • Introduction to Artificial Intelligence
    • Artificial Intelligence in Microsoft Azure

    After completing this module, students will be able to:

    • Describe Artificial Intelligence workloads and considerations

    Module 2: Explore Fundamentals of 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.

    Lessons

    • Introduction to Machine Learning
    • Azure Machine Learning

    After completing this module, students will be able to:

    • Describe fundamental principles of machine learning on Azure

    Module 3: Explore Fundamentals of Computer Vision

    Computer vision is a 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.

    Lessons

    • Computer Vision Concepts
    • Creating Computer Vision solutions in Azure

    After completing this module, students will be able to:

    • Describe features of computer vision workloads on Azure

    Module 4: Explore Fundamentals of 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.

    Lessons

    • Introduction to Natural Language Processing
    • Building Natural Language Solutions in Azure

    After completing this module, students will be able to:

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