Databricks Certified Data Engineer Associate:practical Guide
 

Hands-On Databricks with PySpark: Delta Lake, Unity Catalog & ETL Pipelines
What you'll learn
✓ Understand the Databricks Lakehouse architecture deeply
✓ Navigate and use the Databricks workspace confidently
✓ Write PySpark and SQL to process and transform data
✓ Understand Spark execution plans, transformations, and actions
✓ Apply performance tuning using partitions, repartition, and coalesce
✓ Master Delta Lake with ACID transactions and Time Travel
✓ Implement the Medallion Architecture for production pipelines
✓ Integrate external data sources using AWS S3
✓ Govern data assets using Unity Catalog
✓ Build and schedule automated Databricks Jobs
✓ Create real-time pipelines using Delta Live Tables
✓ Visualize data insights with Genie and BI Dashboards
✓ End-to-End Capstone Project
Requirements
● Basic understanding of SQL
● Basic programming knowledge (Python is helpful)
● Basic understanding of Linux commands
● Basic idea of data engineering or analytics concepts (helpful but not mandatory)
● No prior Databricks or Apache Spark experience required
Description
What's in this course?
The Lakehouse is the future of modern data platforms and Databricks is leading the way as the most powerful and widely adopted unified analytics platform in the industry.
From simple notebook-based data exploration to enterprise-grade, cloud-native data pipelines running on Apache Spark and Delta Lake, Databricks enables teams to ingest, transform, govern, and serve data at scale. This hands-on, project-driven course takes you from absolute beginner to confidently designing and implementing production-ready data engineering pipelines and analytics workflows using Databricks.
You won't just learn theory, you'll
• Navigate the Databricks platform from scratch
• Write PySpark and SQL to process real datasets
• Understand Spark architecture, execution plans, and performance tuning
• Build Delta Lake pipelines with ACID transactions and Time Travel
• Implement the Medallion Architecture (Bronze-Silver-Gold)
• Integrate Databricks with AWS S3 for external data
• Govern data using Unity Catalog
• Build and schedule orchestrated Databricks Jobs
• Visualize insights using Genie and BI Dashboards
• Complete a real-world Capstone Project end to end
By the end of this course, you'll be able to design, build, optimize, and scale Databricks-based data engineering systems just like modern data teams do in real production environments.
What Makes Databricks Powerful?
• Unified platform for data engineering, analytics, and AI
• Apache Spark at its core - the industry standard for big data processing
• Delta Lake for reliable, ACID-compliant data storage
• Lakehouse architecture combining the best of Data Lakes and Data Warehouses
• Built-in orchestration with Databricks Jobs and Delta Live Tables
• Enterprise-grade governance with Unity Catalog
• Seamless cloud integration with AWS, Azure, and GCP
• Collaborative notebooks with multi-language support
This course helps you unlock all of that - step by step.
Special Note
Every concept in this course is demonstrated live. You will
• Sign up and explore the Databricks workspace
• Run real PySpark and SQL transformations on actual datasets
• Build complete Delta Lake pipelines from scratch
• Implement the full Medallion Architecture end to end
• Connect Databricks to GitHub and AWS S3
• Schedule and monitor production-grade jobs
• Complete a full Capstone Project
By the end, you won't just "use Databricks" - you'll operate it like it's used in production data engineering environments.
Course Structure
• Concept-based lectures
• Hands-on demonstrations
• Real-world Capstone Project
Course Contents
• Getting Started with Databricks
• Understanding Spark Fundamentals
• Understanding Spark Execution Basics
• Performance Basics
• Data Warehousing Fundamentals
• Delta Lake and Data Management
• Governance, BI and Pipelines
• Orchestration in Databricks
• Capstone Project
All sections of this course are demonstrated live, with the goal of encouraging enrolled users to set up their own environments, complete the exercises and learn through hands-on experience!
Who this course is for
■ Beginners who want to learn Databricks from scratch
■ Data Engineers who want to build scalable pipelines
■ Data Analysts moving into data engineering
■ SQL developers transitioning to big data processing
■ Anyone preparing for Databricks Certified Associate Exam
■ Cloud Engineers working with AWS, Azure, or GCP data platforms