Developing AI Agents on Azure–Advanced Level: RAG, Azure OpenAI and industrialisation

FAQ–Frequently asked questions about the Developing AI Agents on Azure–Advanced training Who is this advanced Azure AI agents training for?

This training is for experienced developers, Cloud architects, DevOps Engineers, AI consultants and Tech Leads who want to design, deploy and industrialise robust AI agents in production on Azure. It is not an introductory course but an advanced technical path.

What are the technical prerequisites?

Good command of Azure (App Service, Storage, Key Vault, managed identities), solid knowledge of REST APIs and programming (C#, Python or JavaScript/TypeScript). Notions of databases and Docker containers are a plus but not essential.

What is the RAG covered in the training?

RAG (Retrieval-Augmented Generation) is an architecture that lets an AI agent answer using the company’s internal documents without retraining the model. The training covers ingestion, chunking strategies, indexing in Azure AI Search and hybrid vector search (vector + keyword).

How long is the training?

The training lasts 3 days (18 hours), remote with recorded sessions or on-site at your premises. It combines theory, demonstrations and production-oriented hands-on labs.

{"@context":"https://schema.org","@type":"FAQPage","mainEntity":[{"@type":"Question","name":"Who is this advanced Azure AI agents training for?","acceptedAnswer":{"@type":"Answer","text":"This training is for experienced developers, Cloud architects, DevOps Engineers, AI consultants and Tech Leads who want to design, deploy and industrialise robust AI agents in production on Azure. It is not an introductory course but an advanced technical path."}},{"@type":"Question","name":"What are the technical prerequisites?","acceptedAnswer":{"@type":"Answer","text":"Good command of Azure (App Service, Storage, Key Vault, managed identities), solid knowledge of REST APIs and programming (C#, Python or JavaScript/TypeScript). Notions of databases and Docker containers are a plus but not essential."}},{"@type":"Question","name":"What is the RAG covered in the training?","acceptedAnswer":{"@type":"Answer","text":"RAG (Retrieval-Augmented Generation) is an architecture that lets an AI agent answer using the company’s internal documents without retraining the model. The training covers ingestion, chunking strategies, indexing in Azure AI Search and hybrid vector search (vector + keyword)."}},{"@type":"Question","name":"How long is the training?","acceptedAnswer":{"@type":"Answer","text":"The training lasts 3 days (18 hours), remote with recorded sessions or on-site at your premises. It combines theory, demonstrations and production-oriented hands-on labs."}}]} .elementor-accordion .elementor-tab-title .elementor-accordion-icon{margin-right:10px}.elementor-accordion .elementor-tab-title .elementor-accordion-icon + a,.elementor-accordion .elementor-tab-title .elementor-accordion-title{padding-left:4px}

Good to know

Our sessions are guaranteed from a single registrant, with no risk of postponement (except in cases of force majeure). A prior interview takes place between the participant and a company representative to fully take into account the participant’s profile (level, needs, professional context, challenges, etc.). Evaluation: during the training, the trainer assesses participants’ learning progress through quizzes, role-plays and practical exercises. Participants receive a certificate of achievement at the end of the training. This training is part of our Artificial Intelligence training catalogue.

Objectives of the Developing AI Agents on Azure–Advanced training

• By the end of the training, the participant will be able to:
• Understand the architecture of modern AI agents (LLMs, embeddings, vectors, RAG vs fine-tuning).
• Design and implement a complete RAG system (ingestion, chunking, indexing, vector search).
• Connect Azure OpenAI to secured internal data sources.
• Deploy a scalable agent to production with Azure App Service or Container Apps.
• Set up security, access management, cost control and monitoring.
• Industrialise the solution through CI/CD, supervision and performance optimisation.
• Measure the performance and answer quality of the agent.

Prerequisites for the Developing AI Agents on Azure–Advanced training

Good command of Azure (App Service, Storage, Key Vault, managed identities). Solid knowledge of REST APIs and programming (C#, Python or JavaScript/TypeScript). Notions of databases and containers (Docker) appreciated. Because every participant is unique, a personalised interview with our expert lets us design a course aligned with their goals, level and challenges.

Target audience of the Developing AI Agents on Azure–Advanced training

Backend and full-stack developers. Cloud and application architects. DevOps Engineers and SREs managing AI platforms. AI consultants moving to industrialisation. Tech Leads steering AI project teams.