Microsoft Azure AI Fundamentals Training (AI 109)

AI-109 is an entry-level course designed to introduce participants to core Artificial Intelligence (AI) concepts and Microsoft Azure AI services. This course provides foundational knowledge in machine learning, computer vision, natural language processing, and generative AI using Azure tools.

This course is ideal for beginners looking to understand AI workloads and how they are implemented on Microsoft Azure. It covers practical use cases and hands-on labs to explore Azure AI services such as Vision, Language, Speech, and Azure OpenAI.

Participants will gain a strong understanding of AI concepts without needing deep technical or programming experience.

Module 1: Introduction to Artificial Intelligence

Topics Covered:

• What is AI?
• AI workloads and real-world applications
• Responsible AI principles

Lab:

• Explore AI use cases in Azure
• Identify AI workloads (vision, language, speech)
• Navigate Azure AI portal

Outcome:
Understand AI fundamentals and use cases.

Module 2: Machine Learning Basics on Azure

Topics Covered:

• Machine learning concepts
• Training and evaluation
• Azure Machine Learning basics

Lab:

• Create a simple ML model using Azure ML Studio
• Train and evaluate a model
• Deploy a basic ML endpoint

Outcome:
Understand how machine learning models are built and used.

Module 3: Computer Vision on Azure

Topics Covered:

• Image analysis
• Object detection
• OCR (text extraction from images)

Lab:

• Use Vision Studio to analyze images
• Extract text from images
• Build an image recognition app

Outcome:
Learn how AI can interpret visual data.

Module 4: Natural Language Processing (NLP)

Topics Covered:

• Text analytics
• Sentiment analysis
• Key phrase extraction
• Language understanding

Lab:

• Analyze customer feedback using sentiment analysis
• Extract key phrases
• Build a simple text processing solution

Outcome:
Understand how AI processes human language.

Module 5: Speech AI Services

Topics Covered:

• Speech recognition
• Text-to-speech
• Speech translation

Lab:

• Convert speech to text
• Generate voice output from text
• Build a simple voice application

Outcome:
Build applications that can listen and speak.

Module 6: Generative AI with Azure OpenAI

Topics Covered:

• Introduction to Generative AI
• Prompt engineering basics
• Use cases of GPT models

Lab:

• Create a text generation application
• Experiment with prompts
• Build a simple chatbot

Outcome:
Understand and use generative AI capabilities.

Module 7: Responsible AI

Topics Covered:

• Ethics in AI
• Bias and fairness
• Transparency and accountability

Lab:

• Review AI outputs for bias
• Apply responsible AI practices
• Understand compliance requirements

Outcome:
Build ethical and trustworthy AI solutions.