Azure AI Engineer Elite: Microsoft Certified Associate (AI-102) 2026 Mastery
Become an expert in the Azure AI ecosystem and get the skills needed for designing, delivering and managing intelligent solutions using Azure's OpenAI, Azure AI Search and Azure’s Cognitive Services through this credentialing program. You will learn to develop fully autonomous AI agents, implement computer vision technology and be knowledgeable about Natural Language Processing technologies all within enterprise level development on the Azure Cloud Platform.
4.9
By Namifly
Last updated: April 2026
$1200
One-time payment
30-day money-back guarantee
This course includes:
Planning an Azure AI Solution
Generative AI with Azure OpenAI
Developing AI Agents
Natural Language Solutions
Computer Vision Implementation
Document Intelligence
Responsible AI & Content Safety
Final Certification Practice
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Course Description
The Engineering Intelligence through Azure program should be an independent program from all other engineering programs.
As we move towards 2026, the role of a Microsoft AI Engineer has evolved from simply integrating APIs to being responsible for orchestrating fully realised artificial intelligence systems.
The Microsoft Engineering Intelligence through Azure program at Namifly is based upon the following guiding principles: use of the AI-102 syllabus; integration of the Semantic Kernel; and incorporating the tangible knowledge gained from using the AI Foundry to create secure, scalable and responsible artificial intelligence systems.
In addition to updating the AI-102 exam domains, Microsoft has also updated the exam content to include the concept of ‘Agentic Revolution’ that has taken place since the inception of the AI-102 certification exams. The course content has been modified and split into these four technology (core) pillars.
The 2026 Exam Domains
Microsoft has refreshed the AI-102 exam to reflect the "Agentic Revolution." The program is now divided into these critical technical pillars:
Generative AI Solutions (30-35%): This is the heart of the modern exam. You will learn to deploy Azure OpenAI models (GPT-4o, o1), implement RAG (Retrieval-Augmented Generation) using Azure AI Search, and manage prompt engineering and model fine-tuning.
Agentic Frameworks (New for 2026): Master the development of autonomous agents using the Semantic Kernel SDK. Learn how to give AI agents "Tools" and "Plugins" so they can perform real-world tasks like querying databases or sending emails autonomously.
Natural Language Processing (NLP): Build solutions for sentiment analysis, entity recognition, and multi-language translation. You will leverage Azure AI Language to extract deep meaning from unstructured text.
Computer Vision: Implement image classification, object detection, and facial analysis using Azure AI Vision. Learn to process video streams in real-time for security and analytics applications.
Knowledge Mining & Document Intelligence: Use Azure AI Search and Document Intelligence to turn piles of PDFs and documents into a searchable, structured knowledge base for your AI.
Why Get Certified in 2026?
"At Namifly, we emphasize on using AI responsibly. By 2026, Microsoft will require all its engineers to have implemented their new Content Safety filter as well as use their new transparency with AI technologies, in order for them to qualify for the new 'industry passport' issued by the Microsoft Corporation's partners (Fortune 500 companies) that will allow them to create AI solutions that are not only smart but safe and compliant."
Course Curriculum
Expand the sections below to see the detailed curriculum for this course.
Selecting the right AI Service (Language, Vision, Search).
Managing Security: Managed Identities and API Keys.
Deploying and Scaling GPT-4o and o1 models.
Implementing RAG pipelines with Vector Search.
Using Semantic Kernel to orchestrate agents.
Building "Native Plugins" and "Function Calling."
Text Analytics, Summarization, and Named Entity Recognition.
Creating Conversational AI with Azure AI Bot Service.
Custom Vision: Training models for specific industry needs.
Video Indexer for metadata extraction.
Automating data extraction from forms and receipts.
Knowledge Mining: Indexing and AI Enrichments.
Detecting and blocking harmful content with Azure AI Content Safety.
Monitoring AI performance and bias
AI-102 Case Studies and Scenario-based Mock Exams.
Instructor information not available.
4.9
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Frequently Asked Questions
Find answers to common questions about this course.
Microsoft regularly updates the exam. While specific versions retire, the Azure AI Engineer Associate credential is a core part of Microsoft’s 2026 cloud strategy. Our course always covers the absolute latest objectives and "Applied Skills."
Yes, a basic understanding of Python or C# is required. You will be using SDKs and REST APIs to integrate AI services into applications.
AI-900 (Fundamentals) is for everyone to understand AI concepts. AI-102 is a technical, associate-level certification specifically for developers and engineers building the actual systems
This course focuses on the Microsoft/Azure ecosystem, specifically using Semantic Kernel and Azure OpenAI to build "Agentic" solutions, which is Microsoft's direct answer to autonomous agent needs.
