Azure AI Engineer Associate (AI-102)

Learning objectives

At the end of this training, participants will be able to:

• Understand the basic concepts of artificial intelligence and machine learning.
• Explore Azure Cognitive Services, including Vision, Speech and Language.
• Use Azure Machine Learning to create and deploy machine learning models.
• Deploy and integrate AI solutions into Azure cloud-based applications.
• Prepare effectively for the AI-102 exam to obtain certification.

Who this programme is for

The training is aimed at a wide audience, including:

• Beginners in artificial intelligence wishing to acquire practical skills on Azure.
• Developers, technical managers or project leaders wishing to understand the AI services available on Azure.
• IT professionals wishing to prepare for certification Microsoft Azure AI Engineer Associate (AI-102).
• Decision-makers or entrepreneurs interested in AI technologies in a cloud environment.

Prerequisites

No specific prerequisites are required.

Detailed programme

The training takes place intensively over one day and is structured as follows:

Introduction to Artificial Intelligence

• Definition and key concepts of AI, Machine Learning (ML) and Deep Learning.
• Types of algorithms: supervision, non-supervision, reinforcement learning.
• Common applications of AI in companies: natural language processing (NLP), computer vision, recommendations, etc.

Introduction to Azure AI

• Presentation of the main services of Azure for AI: Azure Cognitive Services, Azure Machine Learning.
• Azure Cognitive Services: Computer vision, text analysis, translation, voice recognition, etc.
• Azure Machine Learning: Create, train, deploy ML models on Azure.

Q&A and Demonstration

• Presentation of Azure AI tools in action (Azure Cognitive Services, Azure ML Studio).
• Question-and-answer session.

Use of Azure Cognitive Services

• Computer Vision: Using the image recognition API to detect objects in photos.
• Natural Language Processing (NLP): Text analysis, sentiment extraction, language detection.
• Vocal Recognition: Introduction to voice transcription and synthesis services.

Practical Workshop - Creating a simple AI application

• Practical workshop: Using Azure Cognitive Services to build a simple solution for image recognition or text analysis.
• Group Exercise: Each participant creates a small application using one of the Azure AI services.

Conclusion and Preparation for the AI-102 Review

• Review of the key points of the training.
• Tips for the AI-102 Review: Strategies and Resources for Certification.
• Final Q&A and discussion of opportunities for using Azure AI services in actual projects.

Key takeaways & deliverables

• Accessible approach: Ideal training for beginners with clear pedagogy and theory-practical alternation.
• Acquisition of AI skills: Learn the basics of artificial intelligence and machine learning on the Azure platform.
• Recognized Certification: Validation of your skills with a world-renowned Microsoft certification.
• Practical workshops: Direct experiments with the services of Azure AI for an optimal understanding of tools and solutions.
• Expert trainers: Training provided by qualified professionals, AI experts and Cloud Computing.

Teaching approach

• Live Demonstrations: Interaction with Azure cloud AI services.
• Practical workshops and real case studies: Application of concepts in various sectors.
• Feedback: Sharing best practices and common mistakes in business.
• Simulations and tools: Using IA AZURE resources for interactive workshops.

Assessment & certification

• MCQ at the end of training.
• Practical case studies.
• Continuous evaluation with personalized feedback.

Standards & references

• Azure Well-Architected Framework
• ISO/IEC 19086
• GDPR (General Data Protection Regulation)
• NIST Cloud Computing Standards (SP 500-292)
• ISO 27001 Information security