Updated in May 2025.
This course now features Coursera Coach!
A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course.
Mastering Azure Databricks for Data Engineers equips you with essential skills to excel in Azure Databricks, a top platform for data engineering. By the end of this course, you will be proficient in setting up Databricks services, managing workflows, and utilizing Delta Lake and Databricks tools for effective data engineering.
The course starts with an introduction to data engineering and a thorough exploration of the Databricks platform. You’ll learn how to set up an Azure cloud account, create Databricks workspaces, and understand the architecture. Hands-on activities include creating Spark clusters and using notebooks.
You’ll dive into Databricks File System (DBFS), Unity Catalog, and perform operations on Delta Tables, including time travel and schema evolution. Key topics also include Databricks' incremental ingestion tools and Delta Live Tables (DLT), providing insight into handling large-scale, real-time data processing.
Ideal for data engineers and professionals aiming to expand their Databricks expertise, this course assumes a basic understanding of data engineering and cloud platforms but progresses from foundational concepts to advanced techniques.
Applied Learning Project
The course includes a comprehensive capstone project that simulates real-world data engineering tasks. You'll design data architectures using Azure Databricks, focusing on setting up workspaces, creating Delta Tables, and automating data workflows. The project will require you to implement secure, efficient data ingestion processes and optimize performance with advanced features like Delta Live Tables and CI/CD pipelines.
