Udemy – Apache Iceberg: Complete Hands-On Masterclass

This course offers a practical, hands-on introduction to Apache Iceberg, the modern open table format designed for today’s large-scale data lakes and lakehouses. Whether you’re a data engineer, developer, or architect, this course will help you understand and apply Iceberg concepts through real-world exercises—without the need for any infrastructure setup.

You’ll learn to create, query, and manage Iceberg tables using PySpark in both Databricks Community Edition and Google Colab—two free platforms accessible from your browser. We cover everything from understanding table formats, DDL and DML operations, partition evolution, schema evolution, metadata tables, and Iceberg’s powerful time travel capability.

What You’ll Learn

• Key differences between file formats and table formats in big data
• How to create and manage Apache Iceberg tables using PySpark
• Comparing Hive tables and Iceberg with practical demos
• Running Iceberg on Databricks and Google Colab (setup included)
• Performing DDL and DML operations (insert, update, delete)
• Using Iceberg’s built-in metadata tables to inspect file-level and snapshot info
• Implementing time travel to query historical data versions
• Understanding how Iceberg handles schema evolution and partition changes
• Comparing Iceberg with Delta Lake and Hudi in practical scenarios

• This course is designed for data engineers, data architects, and developers who work with large-scale data pipelines and are looking to modernize their data lake or lakehouse architecture. If you’re currently using Hive, Delta Lake, or Hudi and want to explore a more flexible, scalable, and engine-agnostic table format, this course is for you.
• It’s also ideal for those who want to gain hands-on experience with Apache Iceberg using free tools like Databricks Community Edition and Google Colab — without needing complex infrastructure or cloud setup.
• Whether you’re building batch or streaming pipelines, working on schema evolution, or just want to understand Iceberg’s time travel and metadata capabilities, this course will help you build practical skills with real-world applications.
• No prior experience with Iceberg is required — just a willingness to learn and some basic familiarity with Python or PySpark.