C1071 AI-900 Azure AI Fundamentals Training

Hands-on Azure AI Fundamentals labs for learners who need a practical introduction to artificial intelligence workloads, machine learning concepts, computer vision, natural language processing, speech, generative AI, responsible AI, and core Microsoft Azure AI services.

Note: The Microsoft AI-900 study guide states that Exam AI-900 retired on 30 June 2026. These labs are maintained as Azure AI fundamentals courseware aligned to the published AI-900 skill guide and practical Azure AI learning outcomes.

Course Information

• Course Code: C1071
• Course Title: AI-900 Azure AI Fundamentals Training
• Duration: 2 days
• Level: Beginner
• Course Registration: AI-900 Azure AI Fundamentals Training
• Reference: Microsoft AI-900 Study Guide

Labs by Microsoft Study Guide Domain

The labs are divided according to the Microsoft AI-900 study guide skill domains published for skills measured as of 2 May 2025.

Domain 1: Describe Artificial Intelligence workloads and considerations (15-20%)

Lab	Title	Study Guide Focus
01	AI Workloads and Responsible AI	Common AI workloads, responsible AI principles

Domain 2: Describe fundamental principles of machine learning on Azure (15-20%)

Lab	Title	Study Guide Focus
02	Machine Learning Fundamentals	Regression, classification, clustering, features, labels, training, validation
03	Azure Machine Learning Overview	Automated ML, data, compute, model management, deployment

Domain 3: Describe features of computer vision workloads on Azure (15-20%)

Lab	Title	Study Guide Focus
04	Computer Vision Workloads	Image classification, object detection, OCR, face detection, Azure AI Vision

Domain 4: Describe features of Natural Language Processing workloads on Azure (15-20%)

Lab	Title	Study Guide Focus
05	Natural Language Processing Workloads	Key phrase extraction, entities, sentiment, language modeling, translation
06	Speech and Conversational AI	Speech recognition, speech synthesis, speech translation, conversational AI

Domain 5: Describe features of generative AI workloads on Azure (20-25%)

Lab	Title	Study Guide Focus
07	Generative AI Fundamentals	Generative AI models, scenarios, responsible AI considerations
08	Azure AI Foundry and Model Catalog	Azure AI Foundry, Azure OpenAI, model catalog, playgrounds, evaluation

Cross-Domain Review and Readiness

Lab	Title	Study Guide Focus
09	AI Service Selection Challenge	Match scenarios to services across all domains
10	Capstone: Azure AI Fundamentals Readiness	Domain review, mini presentation, readiness checklist

Learner Guide

Start with the detailed step-by-step guide:

LG-AI-900-Azure-AI-Fundamentals-Training.md

Repository Structure

.
|-- README.md
|-- LG-AI-900-Azure-AI-Fundamentals-Training.md
`-- labs/
    |-- README.md
    |-- tools.md
    |-- lab-01-ai-workloads-responsible-ai.md                    # Domain 1
    |-- lab-02-machine-learning-fundamentals.md                  # Domain 2
    |-- lab-03-azure-machine-learning-overview.md                # Domain 2
    |-- lab-04-computer-vision-workloads.md                      # Domain 3
    |-- lab-05-natural-language-processing-workloads.md          # Domain 4
    |-- lab-06-speech-conversational-ai.md                       # Domain 4
    |-- lab-07-generative-ai-fundamentals.md                     # Domain 5
    |-- lab-08-azure-ai-foundry-model-catalog.md                 # Domain 5
    |-- lab-09-ai-service-selection-challenge.md                 # Cross-domain
    `-- lab-10-capstone-azure-ai-fundamentals-readiness.md       # Cross-domain

Learning Outcomes

After completing the labs, learners will be able to:

• Describe common AI workloads and responsible AI considerations.
• Explain machine learning concepts such as features, labels, training data, and validation data.
• Identify regression, classification, clustering, deep learning, and transformer scenarios.
• Describe Azure AI services for vision, language, speech, and generative AI workloads.
• Recognize when Azure Machine Learning, Azure AI Foundry, and Azure OpenAI are suitable.
• Match business requirements to suitable Azure AI services.
• Prepare a concise Azure AI fundamentals revision summary.