DP-3028 Implement Generative AI engineering with Azure Databricks
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Upcoming Class Schedule
$695.00
Dec 14 - Dec 14, 2026
9:00 AM - 5:00 PM America/New_York- VILT
Who should attend DP-3028 Implement Generative AI engineering with Azure Databricks Course
This Course Overview
This course is designed for data scientists, machine learning engineers, and other AI practitioners who want to build generative AI applications using Azure Databricks. It is intended for professionals familiar with fundamental AI concepts and the Azure Databricks platform.
Prerequisites for DP-3028 Implement Generative AI engineering with Azure Databricks Course
DP-3028 Implement Generative AI engineering with Azure Databricks Course Outline
- Understand Generative AI
- Understand Large Language Models (LLMs)
- Identify key components of LLM applications
- Use LLMs for Natural Language Processing (NLP) tasks
- Explore the main concepts of a RAG workflow
- Prepare your data for RAG
- Find relevant data with vector search
- Rerank your retrieved results
- What are multi-stage reasoning systems?
- Explore LangChain
- Explore LlamaIndex
- Explore Haystack
- Explore the DSPy framework
- What is fine-tuning?
- Prepare your data for fine-tuning
- Fine-tune an Azure OpenAI model
- Explore LLM evaluation
- Evaluate LLMs and AI systems
- Evaluate LLMs with standard metrics
- Describe LLM-as-a-judge for evaluation
- What is responsible AI?
- Identify risks
- Mitigate issues
- Use key security tooling to protect your AI systems
- Transition from traditional MLOps to LLMOps
- Understand model deployments
- Describe MLflow deployment capabilities
- Use Unity Catalog to manage models
Resources
FAQs on DP-3028 Implement Generative AI engineering with Azure Databricks
Participants should be familiar with fundamental Azure Databricks concepts before starting this course.
This course is designed for data scientists, machine learning engineers, and AI practitioners who want to build generative AI applications using Azure Databricks and are familiar with fundamental AI concepts and the Azure Databricks platform.
The course covers language models in Azure Databricks, implementing Retrieval Augmented Generation (RAG), multi-stage reasoning systems (LangChain, LlamaIndex, Haystack, DSPy), fine-tuning language models, and evaluating LLMs using standard metrics and LLM-as-a-judge techniques.
Yes, the course includes a dedicated module on fine-tuning, covering data preparation and hands-on fine-tuning of an Azure OpenAI model.
The course explores LangChain, LlamaIndex, Haystack, and the DSPy framework for building multi-stage reasoning systems.