DP-3028: Implement GenAI Engineering with Azure Databricks

The DP-3028: Implement Generative AI Engineering with Azure Databricks course teaches data professionals how to build generative AI solutions on Azure Databricks. This 8-hour hands-on course covers LLM fine-tuning, Retrieval-Augmented Generation patterns, vector databases, and MLflow for GenAI model lifecycle management. Esamatic srl, a Microsoft Learning Partner in Milan, delivers this course with Microsoft Certified Trainers.

• Applied Skills Credential: validates competency in implementing generative AI engineering on Azure Databricks
• LLM Fine-Tuning: customizing large language models for domain-specific tasks on Databricks
• RAG Patterns: implementing Retrieval-Augmented Generation for knowledge-grounded AI responses
• Vector Databases: creating and managing vector search indexes for semantic retrieval
• MLflow for GenAI: tracking experiments, managing models, and deploying GenAI solutions at scale

Course Overview: DP-3028 Implement GenAI Engineering with Azure Databricks

Azure Databricks provides an integrated platform for building, training, and deploying generative AI applications with enterprise-grade security and governance. The DP-3028 course provides practical experience fine-tuning LLMs, implementing RAG architectures with vector search, managing GenAI model lifecycles with MLflow, and deploying production-ready generative AI solutions on the Databricks platform.

Learning Objectives

1. Fine-tune large language models — customize foundation models for domain-specific use cases using Databricks training infrastructure and techniques
2. Implement RAG architectures — build Retrieval-Augmented Generation pipelines that combine vector search with LLM inference for accurate, grounded responses
3. Manage vector databases and embeddings — create vector search indexes, generate embeddings, and implement semantic retrieval for knowledge bases
4. Deploy GenAI solutions with MLflow — track experiments, register models, and deploy generative AI endpoints using MLflow and Databricks Model Serving

Who Should Attend

This course is ideal for data engineers, ML engineers, and AI developers who want to build and deploy generative AI applications using the Azure Databricks platform.

Career Benefits

Generative AI engineering is the fastest-growing specialty in data and AI. The DP-3028 Applied Skills credential validates practical ability to implement GenAI solutions on Databricks — a competency in extraordinary demand for AI engineers, ML platform specialists, and GenAI architects.

Prerequisites

• Experience with Azure Databricks and Apache Spark
• Understanding of machine learning fundamentals and model training
• Familiarity with Python programming and data manipulation
• Basic knowledge of natural language processing concepts

Frequently Asked Questions

What is the DP-3028 Applied Skills credential?

The DP-3028 is a Microsoft Applied Skills credential that validates hands-on ability to implement generative AI engineering solutions on Azure Databricks. It is earned through a performance-based lab assessment.

What is Retrieval-Augmented Generation (RAG)?

RAG is an architecture pattern that enhances LLM responses by retrieving relevant documents from a knowledge base and providing them as context. This reduces hallucination and enables domain-specific answers without fine-tuning.

Do I need Databricks experience for DP-3028?

Yes, familiarity with Azure Databricks and Apache Spark is recommended. The course builds on Databricks platform knowledge to implement GenAI-specific solutions.

Does the DP-3028 credential expire?

Microsoft Applied Skills credentials are valid for one year from the date earned and can be renewed through reassessment.