What you'll learn

• Provision and configure Azure OpenAI Service deployments for GPT-4, GPT-4o and embedding models.
• Apply prompt engineering techniques: system messages, few-shot prompting and chain-of-thought.
• Build Retrieval Augmented Generation (RAG) solutions with Azure AI Search and OpenAI embeddings.
• Develop AI assistants using the Azure OpenAI Assistants API with function calling and file search.
• Apply responsible AI principles: content filtering, groundedness detection and safety evaluation.

Who should attend?

This training is designed for developers, AI engineers and architects who want to build enterprise-grade Generative AI applications on Azure. It is also ideal for AI leads and technical project managers driving GenAI initiatives within their organisations.

Prerequisites

• Azure AI-900 or AI-102 recommended but not mandatory.
• Basic Python programming skills.
• General understanding of large language models (LLMs) is helpful.

Course curriculum

Module 1 – Azure OpenAI Service fundamentals

Overview of Azure OpenAI, available models (GPT-4, GPT-4o, embeddings), provisioning deployments, quotas and API authentication.

Module 2 – Prompt engineering

System messages, few-shot prompting, chain-of-thought, temperature and parameter tuning, and avoiding common prompt pitfalls.

Module 3 – Building GenAI applications

Using the Azure OpenAI SDK and REST API in Python, streaming completions, structured outputs and integrating with existing applications.

Module 4 – Retrieval Augmented Generation (RAG)

Creating vector indexes with Azure AI Search, generating embeddings, building RAG pipelines and grounding responses in enterprise data.

Module 5 – AI Assistants & function calling

Designing Azure OpenAI Assistants with tools, function calling for real-time data, file search and managing conversation state.

Module 6 – Responsible AI & assessment prep

Azure OpenAI content filters, groundedness evaluation, safety and compliance considerations, and Applied Skills assessment preparation.

Certification exam

• Assessment: Microsoft Applied Skills – Develop Generative AI Solutions with Azure OpenAI Service.
• Format: Lab-based applied skills assessment.
• Duration: 2 hours.
• Language: English.
• Credential: Official Microsoft Applied Skills badge.

Why this certification matters

• Earn a Microsoft-recognised credential for Generative AI engineering on Azure.
• Master RAG and prompt engineering — the most in-demand GenAI skills in 2026.
• Build enterprise-ready AI applications grounded in real data.
• Complements AI-102 and positions you as a full-stack Azure AI practitioner.

What's next?

After this credential, learners typically advance to AI-102 Azure AI Engineer Associate, multi-modal AI solution design with Azure AI Foundry, or specialised roles in enterprise GenAI platform engineering.