Luca Gennari

This hands-on course covers DevOps principles, including CI/CD and testing, applied to Databricks data engineering pipelines. It focuses on continuous deployment using the Databricks REST API, SDK, and CLI, specifically incorporating Declarative Automation Bundles (DABs) for streamlined deployment across environments. You will learn to modify, validate, deploy, and execute DABs for multiple configurations using the Databricks CLI. The course also introduces using Visual Studio Code as an IDE for local development and concludes with automating deployment using GitHub Actions and DABs. By the end, you'll be able to automate Databricks project deployments with DABs, improving efficiency through DevOps practices. Note: Hands-on training courses will be updated to reflect the newest product and feature announcements from Data + AI Summit in June 2026. Prerequisites - Strong familiarity with the Databricks Data Intelligence Platform - Intermediate Python programming experience, including designing and implementing functions and classes - Intermediate SQL experience for data analysis and transformation - Experience with data ingestion and transformation using PySpark - Familiarity with…

This hands-on course guides you through deploying and monitoring agentic AI systems in the Databricks environment. You will start by learning how to deploy agents in batch mode using AI Functions and integrate them into data pipelines. Next, you'll explore real-time deployment using Model Serving, including deploying agents as REST endpoints and managing autoscaling, versioning, and governance via Mosaic AI Model Serving. You'll then turn to observability and monitoring, using MLflow tracing and scoring functions to capture metrics, analyze requests and responses, and detect anomalies in production. Finally, you'll learn best practices for deploying agents with built-in trace collection, inference logging, and feedback loops to support ongoing evaluation and robustness. Note: Hands-on training courses will be updated to reflect the newest product and feature announcements from Data + AI Summit in June 2026. Prerequisites - Familiarity with the Databricks Data Intelligence Platform, including Unity Catalog and Delta Lake - Intermediate Python programming experience - Familiarity with Generative AI fundamentals, including LLMs, RAG architectures, and prompt engineering - Familiarity…

In this hands-on course, you will explore core SQL programming and procedural logic skills within Databricks, focusing on how to build modular, maintainable, and production-ready analytics workflows. You’ll start by learning about key SQL constructs—such as Common Table Expressions, temporary views, and User Defined Functions—that make your SQL development cleaner and more reusable. The course then guides you through advanced SQL scripting techniques using compound statements, variables, control flow, conditionals, loops, and robust error handling to create structured and flexible SQL processes. Finally, you’ll discover how to orchestrate and modernize complex workflows with Lakeflow Jobs and migration strategies, transforming legacy tasks into modular, automated pipelines that leverage the full capabilities of the Databricks platform. Note: Hands-on training courses will be updated to reflect the newest product and feature announcements from Data + AI Summit in June 2026. Prerequisites - Familiarity with the Databricks Data Intelligence Platform, including workspaces, SQL warehouses, and notebooks - Experience with Databricks Lakehouse architecture, including Delta Lake and Unity…