719-298-4047info@force7training.com
Student Login
Force7 Training
FRCMIC-1Microsoft

Microsoft Azure AI Fundamentals (AI-900)

In this course, you will: Gain a solid foundation in AI concepts including machine learning, NLP, computer vision, and generative AI.

Duration · 1 dayVirtual + In-PersonInstructor-Led

$650

Course Description

In this course, you will:

Gain a solid foundation in AI concepts including machine learning, NLP, computer vision, and generative AI.

Learn hands-on with Azure AI Foundry to build and test intelligent applications.

Understand real-world applications of AI such as text analysis, speech recognition, image analysis, and information extraction.

Explore responsible AI practices to design solutions that are ethical and trustworthy.

Prepare for more advanced AI projects by establishing a strong base in both theory and Azure tools.

— Be First in Line —

Register Your Interest

We're finalizing the schedule for Microsoft Azure AI Fundamentals (AI-900). Add your details below and we'll notify you the moment a session opens for registration — no payment or commitment required.

Audience Profile

This course is intended for:

  • Business professionals
  • IT professionals
  • managers
  • analysts
  • developers
  • students
  • anyone seeking foundational knowledge of Artificial Intelligence and Microsoft Azure AI services. No prior AI experience required.

Prerequisites

Before enrolling, you should have:

  • Prerequisite certification is not required before taking this course. However, successful Azure AI Fundamental students start with essential knowledge of computing and internet concepts and an interest in using Azure AI services.
  • Before taking this course, students should have:
  • 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.

— What You'll Learn —

Learning Objectives

In this course, you will learn to:

  • 1Upon completion of this course, students will be able to:
  • 2Describe common Artificial Intelligence workloads and use cases
  • 3Understand Microsoft's Responsible AI principles
  • 4Explain fundamental machine learning concepts
  • 5Identify Azure services for machine learning solutions
  • 6Describe computer vision capabilities in Azure
  • 7Understand Natural Language Processing (NLP) workloads
  • 8Explore Generative AI concepts and Azure AI services
  • 9Prepare for the Microsoft AI-900 certification exam objectives

— Day-by-Day —

Course Outline

Module 1

Introduction to Artificial Intelligence

  • What is Artificial Intelligence?
  • AI in everyday business applications
  • Common AI workloads
  • Machine Learning
  • Computer Vision
  • Natural Language Processing
  • Conversational AI
  • Generative AI
  • Benefits and challenges of AI adoption
  • Azure AI platform overview
  • Lab / Demonstration
  • Explore Azure AI services portal
  • Review real-world AI business scenarios
  • Knowledge Check
  • Identify appropriate AI workloads for business use cases

Module 2

Responsible AI

  • Microsoft's Responsible AI framework
  • Fairness
  • Reliability and Safety
  • Privacy and Security
  • Inclusiveness
  • Transparency
  • Accountability
  • Lab / Demonstration
  • Analyze AI solution scenarios using Responsible AI principles
  • Knowledge Check
  • Evaluate AI solutions for ethical considerations

Module 3

Machine Learning Fundamentals

  • What is Machine Learning?
  • Types of Machine Learning
  • Regression
  • Classification
  • Clustering
  • Features and Labels
  • Training vs. Validation Data
  • Model Training and Evaluation
  • Understanding accuracy and performance metrics
  • Deep Learning fundamentals
  • Introduction to Transformer models
  • Lab / Demonstration
  • Explore Azure Machine Learning Studio
  • Build a no-code machine learning model
  • Knowledge Check
  • Select the appropriate machine learning approach for various scenarios

Module 4

Azure Machine Learning Services

  • Azure Machine Learning overview
  • Automated Machine Learning (AutoML)
  • Azure Machine Learning Designer
  • Model deployment concepts
  • Machine learning lifecycle
  • Lab / Demonstration
  • Create a no-code predictive model using AutoML
  • Knowledge Check
  • Identify Azure services used throughout the ML lifecycle
  • Lunch Break
  • Duration: 1 Hour

Module 5

Computer Vision Workloads

  • Introduction to Computer Vision
  • Image Classification
  • Object Detection
  • Optical Character Recognition (OCR)
  • Facial Analysis
  • Document Intelligence
  • Azure AI Vision services
  • Lab / Demonstration
  • Analyze images using Azure AI Vision
  • Extract text from images and documents
  • Knowledge Check
  • Match computer vision services to business requirements

Module 6

Natural Language Processing (NLP)

  • Understanding NLP
  • Language Detection
  • Sentiment Analysis
  • Key Phrase Extraction
  • Entity Recognition
  • Text Analytics
  • Translation Services
  • Speech Services
  • Lab / Demonstration
  • Analyze customer feedback using Azure AI Language Services
  • Knowledge Check
  • Select appropriate NLP capabilities for business scenarios

Module 7

Generative AI Fundamentals

  • What is Generative AI?
  • Large Language Models (LLMs)
  • Foundation Models
  • Prompt Engineering Basics
  • Azure OpenAI Service Overview
  • Responsible Generative AI
  • Common Generative AI use cases
  • Content generation
  • Summarization
  • Question answering
  • Copilot experiences
  • Lab / Demonstration
  • Explore prompt engineering examples
  • Demonstrate Azure OpenAI capabilities
  • Knowledge Check
  • Identify appropriate generative AI solutions for business use cases

Module 8

AI-900 Certification Preparation

  • Exam structure and objectives
  • Common exam question types
  • Test-taking strategies
  • Review of key concepts
  • Practice exam questions
  • Final Review
  • AI workloads and Responsible AI
  • Machine Learning fundamentals
  • Computer Vision
  • Natural Language Processing
  • Generative AI services
  • Course Wrap-Up
  • Q&A Session
  • Additional learning resources
  • Certification roadmap:
  • AI-900 Azure AI Fundamentals
  • AI-102 Azure AI Engineer Associate
  • DP-100 Azure Data Scientist Associate

Note: Course outlines are provided as a general guide. Content, pacing, labs, and instructional emphasis may vary based on instructor expertise, student experience levels, and customer-specific learning objectives.

— Keep Exploring —

Need a different angle?

Browse the full Microsoft catalog or chat with an advisor about a custom training plan for your team.