Azure certification track
Develop Generative AI Solutions with Azure OpenAI (AI-050)
Build production-ready Generative AI applications with Azure OpenAI Service. Master prompt engineering, RAG, embeddings and responsible AI for the AI-050 assessment.
Course overview
- Learn to develop, deploy and manage Generative AI applications using Azure OpenAI Service.
- Go from prompt engineering fundamentals to retrieval augmented generation (RAG) and AI assistant design.
- Targeted at the Microsoft Applied Skills credential AI-050, with hands-on labs throughout the day.
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.