Generative AI with Azure Databricks DP-3028 Training Course – Design, Train and Deploy LLM Solutions
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Each session will take place even if only one person is registered (except in cases of force majeure).
Description of the Generative AI with Azure Databricks DP-3028 Training Course
This training course teaches you to implement generative AI solutions on the Azure Databricks platform. You will learn to work with large language models (LLMs), build RAG pipelines, fine-tune models and deploy production-ready AI applications using the tools of the Databricks ecosystem: MLflow, Unity Catalog and Delta Lake.
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Format
Remote (recorded sessions). It is possible to customise the training course for a private group. Contact us for more information.
GOOD TO KNOW
This training course includes numerous exercises (60% practical). All exercises are performed directly on the Azure Databricks platform. You will build end-to-end generative AI pipelines. This training course prepares you for the DP-3028 Microsoft certification.
This training course is part of our Artificial Intelligence Training Courses. Explore our other AI training courses to fully leverage machine learning, LLMs and generative AI.
Objectives of the Generative AI with Azure Databricks DP-3028 Training Course
By the end of this training course, each participant will be able to:
- Work with large language models on Azure Databricks
- Build RAG (Retrieval-Augmented Generation) pipelines
- Fine-tune and customise LLMs
- Use MLflow to track and manage AI models
- Deploy generative AI solutions in production
- Apply responsible AI principles
Prerequisites
- Python programming experience
- Basic understanding of machine learning
- Familiarity with Azure cloud services
- Experience with Databricks recommended
- Because each participant is unique, a personalised interview with our expert allows us to design a training programme perfectly aligned with their objectives, level and professional challenges.
Target Audience
This training course is designed for:
- Data scientists and ML engineers
- Azure architects
- Developers working on AI and data projects
- Profiles preparing for DP-3028 certification
Detailed Programme of the Generative AI with Azure Databricks DP-3028 Training Course
Introduction to LLMs and Generative AI
- Understanding LLMs and their key components.
- Identifying use cases for generative AI in NLP and business applications.
Designing Generative AI Applications
- Designing applications that leverage generative models.
- Using Spark to explore and integrate these models in a collaborative environment.
Building RAG Pipelines
- Understanding RAG workflows and preparing data.
- Setting up vector search and improving response relevance.
Agentic AI Frameworks
- Exploring frameworks such as LangChain, LlamaIndex or Haystack.
- Designing systems capable of solving complex tasks.
Fine-tuning LLMs
- Preparing training data and optimising an Azure OpenAI model.
- Adapting LLMs to specific needs.
Evaluating LLM Performance
- Comparing LLM evaluation with traditional ML.
- Using standard metrics and approaches like “LLM-as-a-judge”.
Responsible AI and Security
- Identifying risks and applying mitigation strategies.
- Implementing security tools to protect AI systems.
Deploying Generative AI in Production
- Understanding deployment models and the transition from MLOps to LLMOps.
- Managing the model lifecycle with MLflow and Unity Catalog.
Practical Workshop
- Creating an LLM-based application.
- Implementing a RAG pipeline.
- Deploying a generative model in production.
FAQ – Generative AI with Azure Databricks (DP-3028) Training
What is Azure Databricks used for?
Azure Databricks is a unified analytics and AI platform on Azure built around Apache Spark, Delta Lake, and MLflow. It is used for data engineering (ETL/ELT), data warehousing (lakehouse), machine learning model training, and increasingly for generative AI applications: building RAG systems, fine-tuning open models, and operationalizing LLMs at scale. MFE-IT trains data engineers and AI practitioners on the DP-3028 generative AI curriculum.
What is the DP-3028 course?
DP-3028 is Microsoft’s official training reference for generative AI with Azure Databricks, covering Vector Search, Mosaic AI Model Serving, Foundation Model APIs, RAG architectures, Unity Catalog governance, and MLflow for AI lifecycle management. The MFE-IT DP-3028 training delivers this curriculum with hands-on practice on real datasets.
How does RAG work on Databricks?
RAG on Databricks uses Vector Search to index your data (powered by Delta tables), retrieves relevant context at query time, then feeds it to an LLM via Mosaic AI Model Serving or Foundation Model APIs. Unity Catalog governs access, MLflow logs evaluations, and AI Gateway centralizes routing and policies. Through MFE-IT’s hands-on approach, learners build a production-grade RAG application during the training.
Is Databricks better than Synapse for AI?
For generative AI specifically, Azure Databricks currently offers a more mature stack with Mosaic AI, Vector Search, and Foundation Model APIs natively integrated. Azure Synapse is stronger for traditional data warehousing and Power BI integration. Many organizations use both. Our MFE-IT training course on generative AI with Azure Databricks DP-3028 explains where each platform fits in a modern data and AI architecture.
Would you like to know about upcoming sessions ?
Would you like to schedule this training course on a specific date ? Contact us by email or by filling out the contact form.