July 2025
Beginner
4h 31m
English
Closed Captioning available in English
Overview
The Databricks Intelligence Platform unifies data, analytics, and AI into a single, collaborative environment, enabling organizations to process large-scale data efficiently. At the heart of this platform, data engineering plays a critical role by ensuring that data is reliably ingested, transformed, and made accessible for artificial intelligence, machine learning, and business analytics. Strong data engineering practices on Databricks enable high-quality, scalable, and governed data pipelines that power real-time decision-making and advanced AI use cases.
In this course, you will master the core concepts and tools needed to build and manage data pipelines on the Databricks Intelligence platform. You will learn how to set up and navigate the environment, work with notebooks and clusters, and use Delta Lake for reliable data storage and processing. The course also covers data ingestion, transformation, and streaming, along with best practices for performance and governance. By the end of this course, you’ll have a solid foundation to design and operate robust data engineering workflows on Databricks.
Course Path
This course is the first step in a two-course series, starting with Data Engineering Fundamentals and moving on to Advanced Data Engineering on Databricks. Together, these courses provide a structured journey from core principles to more complex data engineering techniques, helping you build deeper expertise and confidence working with the Databricks platform.
What You’ll Learn
By the end of this course, you should be able to:
- Use the Databricks Intelligence Platform and its tools
- Ingest data from diverse sources using Lakeflow Connect
- Build ETL pipelines using Lakeflow Spark Declarative Pipelines
- Deploy production workloads using Lakeflow Jobs and Databricks Asset Bundles
- Manage data governance and security using Unity Catalog
Who This Course Is For
This course is for you because:
- You are an entry-level data engineer, data analyst, or AI engineer seeking to gain a fundamental understanding of data engineering tools offered by Databricks.
- You are looking to apply for a new role that utilizes Databricks and want to strengthen your foundational knowledge to stand out in the job market.
- You’re an established data engineer moving from other technologies and aim to apply your skills to Databricks.
Prerequisites
- Basic SQL knowledge
- Basic Python programming experience
- Familiarity with cloud fundamentals
Next Steps
After completing this course, you can continue advancing your knowledge and skills by completing the following resources:
- Databricks Certified Data Engineer Associate Study Guide (Book)
- Databricks Data Engineer Associate Certification Prep in 2 Weeks (Live Event)
- Advanced Data Engineering on Databricks (Course)
About the Instructor
Derar Alhussein is a Lead Data Engineer with a master’s degree in Data Mining and over a decade of hands-on experience in data and AI projects. He is a Databricks MVP and holds ten certifications from Databricks, demonstrating his strong expertise in the field. Derar is also the author of the O’Reilly book “Databricks Certified Data Engineer Associate Study Guide”. In addition, he is an experienced instructor, with a proven track record of success in training thousands of data professionals, helping them to develop their skills and obtain industry-recognized certifications.
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