AI-900: Microsoft AI Fundamentals MTA (Microsoft Training After-hours) Course Outline
Special Note to New Hampshire ResidentsThis course has not yet been approved by the New Hampshire Department of Education. Please contact us for an update on when the class will be available in New Hampshire.
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.
This event is delivered in our hybrid Microsoft Training After-hours (MTA) format that blends one late-day/evening session with the live instructor presentation, followed by on-demand training and a TA session for questions and problem-solving.
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 dont 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, Data Scientist, Developer, Solutions Architect
Preparation for exam: AI-900
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
Describe features of conversational AI workloads on Azure
Prerequisites
Familiarity with computers and using a web browser.
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 workload associated with AI. You'll then explore considerations and principles for responsible AI development.
Lessons
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.
Lessons
Introduction to Machine Learning
Azure Machine Learning
Module 3: 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
Computer Vision in Azure
Module 4: 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.
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.
Lessons
Conversational AI Concepts
Conversational AI in Azure
View outline in Word
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