Training: Implement Generative AI engineering with Azure Databricks (DP-3028)

Unlock the full potential of generative models in Azure

Large language models are deeply transforming how we work in analytics, data science, and artificial intelligence. With Azure Databricks, these technologies are now available in a powerful and collaborative cloud environment. This training offers a hands-on, structured approach to understanding and implementing generative models in real-world use cases.

Unlike a simple introduction to AI, this program is designed for professionals who want to go further. It enables you to master not only the models themselves, but also the entire surrounding ecosystem: data management, performance evaluation, optimization, security, governance, and deployment. You will learn to think like a modern AI engineer, capable of integrating complex components into a robust pipeline.

Build AI solutions focused on quality and responsibility

Today, building a high-performing model is no longer enough. It also needs to be interpretable, reliable, and ethically compliant. That’s why part of the program is dedicated to responsible AI. You’ll learn how to identify risks, integrate security tools, and design models aligned with industry best practices. Azure Databricks provides key features to help you implement these standards.

You’ll also discover how to structure your data to improve the relevance of your models. The fine-tuning approach allows you to adapt an existing model to a specific business case without having to rebuild it from scratch. This strategy saves time, reduces resource usage, and delivers much more accurate results.

An architecture built for scalability and deployment

AI engineering doesn’t stop at model training. You also need to think about production. That’s why the training includes a complete module dedicated to LLMOps. You’ll learn how to deploy your models in Azure using MLflow, track their performance over time, and automate updates. Unity Catalog will help you centralize the management of models, access rights, and resources.

One of Azure Databricks’ key strengths is its ability to combine advanced data processing tools with cutting-edge AI models. By learning to leverage this synergy, you’ll be able to create intelligent solutions that connect to your data sources and integrate seamlessly with your cloud infrastructure.

A hands-on training program for rapid upskilling

This program is structured to help participants quickly build their skills. Each topic covers a key area of modern AI engineering. You’ll discover tools like LangChain, LlamaIndex, and Haystack, which allow for complex reasoning workflows. You’ll also learn to objectively evaluate your models using appropriate metrics and approaches such as LLM-as-a-judge.

Thanks to practical exercises, you’ll know how to apply the concepts to your internal projects. The goal isn’t just to understand, but to build. And above all, to replicate these methods in various contexts while meeting quality, ethical, and scalability requirements.

FAQ

Is this training accessible to non-developers?
Yes. If you already have a basic understanding of AI and data handling, you can follow the program even without being an experienced developer.

How is this course different from a standard Azure course?
This course focuses on generative AI and language models. It goes far beyond simply using Azure. It teaches you how to build, fine-tune, secure, and deploy advanced models.

Can I apply these skills in my company?
Absolutely. The content is designed for real-world application, with tools, techniques, and workflows that can be directly used in enterprise AI projects — whether in development, research, or production.