Recommended Course: Azure Databricks & Spark for Data Engineers by Ramesh Retnasamy (Udemy)

Reading about Databricks only gets you so far. You learn it properly by building something end to end. That’s why this Udemy course by Ramesh Retnasamy is the one I suggest to engineers who want practical Azure Databricks skills.

The resource

• Title: Azure Databricks & Spark for Data Engineers: Hands-on Project
• Provider: Udemy
• Instructor: Ramesh Retnasamy
• Link: Azure Databricks & Spark for Data Engineers on Udemy

What it covers

The whole course is built around a real-world project using Formula 1 motor racing data. Along the way it covers:

• Azure Databricks compute, notebooks and jobs
• Ingesting and transforming data with PySpark and Spark SQL
• Delta Lake and incremental data processing
• Lakehouse design using the medallion (bronze, silver and gold) architecture
• Unity Catalog for organising and governing data
• Orchestrating pipelines with Lakeflow Jobs, with Azure Data Lake Storage Gen2 and Azure Data Factory alongside

The course page says it has been rebuilt around current Databricks features such as Unity Catalog and Lakeflow Jobs instead of legacy approaches like the Hive metastore. For me that matters, because many older tutorials still teach patterns I’d no longer use on a new platform.

Who it’s for

It’s aimed at data engineers and developers who know basic Python and SQL. Cloud experience helps but isn’t essential, and you don’t need any previous Databricks experience. You’ll need an Azure subscription to follow along.

My take

What I like most is that it follows the same path a real project does: set up the environment, land raw data, clean it, model it and orchestrate it. That’s much closer to day-to-day work than isolated feature demos. Once you finish, apply the same pattern to a dataset from your own domain, and add the governance pieces (groups, grants and naming conventions) that a production platform needs.

If you work on Microsoft Fabric rather than Databricks, the course is still worth your time. Spark, Delta Lake and the medallion pattern carry over directly, and only the platform-specific parts differ.

This is an independent recommendation. I’m not affiliated with Udemy or the instructor.