Introduction to AI in Azure

Course Overview

1 - Introduction to AI concepts

• Generative AI and agents
• Text and natural language
• Speech
• Computer vision
• Information extraction
• Responsible AI
• Module assessment

2 - Introduction to generative AI and agents

• Large language models (LLMs)
• Prompts
• AI agents
• Module assessment

3 - Introduction to natural language processing concepts

• Tokenization
• Statistical text analysis.
• Semantic language models
• Module assessment

4 - Introduction to AI speech concepts

• Speech-enabled solutions
• Speech recognition
• Speech synthesis
• Module assessment

5 - Introduction to computer vision concepts

• Computer vision tasks and techniques
• Images and image processing
• Convolutional neural networks
• Vision transformers and multimodal models
• Image generation
• Module assessment

6 - Introduction to AI-powered information extraction concepts

• Overview of information extraction
• Optical character recognition (OCR)
• Field extraction and mapping
• Module assessment

7 - Get started with AI in Azure

• Understand Azure
• Developing AI apps on Azure
• Microsoft Foundry for AI
• Using Microsoft Foundry endpoints

8 - Get started with generative AI and agents in Azure

• Generative AI models
• Using a generative AI model
• Creating an agent

9 - Get started with text analysis in Azure

• Azure Language
• Azure Language SDK
• Azure Language MCP
• Module assessment

10 - Get started with speech in Azure

• Speech recognition
• Speech synthesis
• Creating a speech-capable agent
• Module assessment

11 - Get started with computer vision in Azure

• Multimodal models for image analysis
• Image generation models
• Video generation models
• Module assessment

12 - Get started with AI-powered information extraction in Azure

• Extract information from documents
• Extract information from audio and video
• Module assessment

Prerequisites

There are no required prerequisites. Success in this course is supported by:

• Experience using computers and the internet
  Interest in AI workloads and applications
  A basic understanding of math (interpreting charts, simple probability)
  Familiarity with fundamental programming concepts (helpful but not required)