Generative AI Engineering with Databricks
This course is aimed at data scientists, machine learning engineers, and other data practitioners who want to build generative AI applications using the latest and most popular frameworks and Databricks capabilities.
Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures in the first three modules. You can access the lecture notebooks in the Vocareum lab environment.
Below, we describe each of the four, four-hour modules included in this course.
Building Retrieval Agents On Databricks: This course provides hands-on training for building retrieval agents on the Databricks Data Intelligence Platform. Participants will learn to parse unstructured documents into structured data, transform and chunk content for retrieval workflows, build vector search solutions for document retrieval, and develop production-ready agents using MLflow and Agent Bricks. The course covers the complete agent lifecycle from document processing through embedding generation, vector indexing, and agent deployment with governance capabilities.
Building Single-Agent Applications on Databricks: This course provides hands-on training for building single-agent applications on the Databricks Data Intelligence Platform. Students will learn to create AI agents that leverage Unity Catalog functions as tools, implement comprehensive tracing and monitoring with MLflow, and deploy agents using both traditional frameworks like LangChain and modern solutions like Agent Bricks. The course covers the complete agent lifecycle from initial tool creation and testing in AI Playground through production deployment with governance, evaluation, and continuous improvement capabilities.
Agent Evaluation on Databricks: This course teaches students how to systematically evaluate AI agents using MLflow's evaluation framework, addressing the unique challenges of non-deterministic AI systems that traditional software testing cannot handle. Students learn to implement various evaluation approaches including built-in judges for common criteria like correctness and safety, guideline judges for business-specific requirements, and custom judges for specialized needs. The course covers both offline evaluation using curated datasets and online production monitoring, with hands-on experience using MLflow's tracing capabilities to understand agent execution patterns and collect human feedback from different stakeholder types. Through practical demonstrations and labs, students develop skills in creating evaluation workflows that drive continuous quality improvements throughout the AI agent development lifecycle.
Generative AI Application Deployment and Monitoring: Ready to learn how to deploy, operationalize, and monitor generative deploying, operationalizing, and monitoring generative AI applications? This module will help you gain skills in the deployment of generative AI applications using tools like Model Serving. We’ll also cover how to operationalize generative AI applications following best practices and recommended architectures. Finally, we’ll discuss the idea of monitoring generative AI applications and their components using Lakehouse Monitoring.
• Ability to write production-quality Python code, including OOP, exception handling, decorators, type hints, and proper documentation.
• Experience writing advanced SQL SELECT queries, handling data types and NULL values, and creating reusable, well-documented SQL functions.
• Comfort navigating the Databricks workspace and notebooks, managing compute, using Catalog Explorer, and understanding Databricks-managed services.
• Understanding of LLM behavior, basic prompt engineering, RAG concepts, agent reasoning, and working with REST APIs and JSON payloads.
• Basic familiarity with MLflow, agent frameworks (e.g., LangChain), and recommended Databricks training such as AI Agents Fundamentals.
• Familiarity with natural language processing concepts
• Familiarity with prompt engineering/prompt engineering best practices
• Familiarity with the Databricks Data Intelligence Platform
• Familiarity with RAG (preparing data, building a RAG architecture, concepts like embedding, vectors, vector databases, etc.)
• Experience with building LLM applications using multi-stage reasoning LLM chains and agents
• Experience with Databricks Data Intelligence Platform tools for evaluation and governance.
• Understanding of Unity Catalog concepts including catalogs and schemas
• Basic knowledge of MLflow
Outline
Building Retrieval Agents On Databricks
• Document Parsing and Chunking
• Vector Search for Retrieval
• Building and Logging Retrieval Agents
• Agent Bricks
Building Single-Agent Applications on Databricks
• Foundations of Agents
• Building Single Agents
• Reproducible Agents
• Production-Ready Agents with Agent Bricks
Agent Evaluation on Databricks
• AI Agent Evaluation Fundamentals
• Built-In and Guideline Judges
• Custom Judges and Human Feedback
Generative AI Application Deployment and Monitoring
• Model Deployment Fundamentals
• Batch Deployment
• Real-Time Deployment
• AI System Monitoring
• LLMOps Concepts
Upcoming Public Classes
Date | Time | Your Local Time | Language | Price |
|---|---|---|---|---|
May 26 - 29 | 01 PM - 05 PM (Europe/London) | - | English | $1500.00 |
Jun 09 - 12 | 11 AM - 03 PM (Asia/Singapore) | - | English | $1500.00 |
Jun 09 - 10 | 09 AM - 05 PM (Europe/London) | - | English | $1500.00 |
Jun 09 - 12 | 08 AM - 12 PM (America/Los_Angeles) | - | English | $1500.00 |
Jun 23 - 26 | 01 PM - 05 PM (Europe/London) | - | English | $1500.00 |
Jul 28 - 31 | 11 AM - 03 PM (Asia/Singapore) | - | English | $1500.00 |
Jul 28 - 31 | 01 PM - 05 PM (Europe/London) | - | English | $1500.00 |
Jul 28 - 31 | 08 AM - 12 PM (America/Los_Angeles) | - | English | $1500.00 |
Jul 30 - 31 | 09 AM - 05 PM (Europe/London) | - | English | $1500.00 |
Public Class Registration
If your company has purchased success credits or has a learning subscription, please fill out the Training Request form. Otherwise, you can register below.
Private Class Request
If your company is interested in private training, please submit a request.
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