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Databricks for Data Engineers: Full Curriculum (Structured)

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“This course contains the use of artificial intelligence”Welcome to the ultimate Data Engineering Bootcamp, designed to take you from foundational concepts to building production-grade data systems used in real-world companies. In this course, you won’t just learn theory—you’ll build end-to-end data pipelines, work with Databricks, and deliver business-ready dashboards using modern tools and best practices. We start with the fundamentals of data engineering, including the Medallion Architecture (Bronze, Silver, Gold), and gradually move into advanced topics like ETL vs ELT, batch and streaming pipelines, and incremental processing.

You’ll learn how to work with different data formats like CSV, JSON, and Parquet, and how to design efficient pipelines using Apache Spark. We’ll also cover how to build optimized storage using Delta Lake, ensuring your data is reliable, scalable, and ready for analytics. As you progress, you’ll master data optimization techniques such as partitioning, query optimization, caching, and cost optimization strategies like cluster sizing and autoscaling.

These are critical skills used by professional data engineers to improve performance and reduce cloud costs. We also go deep into data governance and security, where you’ll learn how to use Unity Catalog, implement role-based access control (RBAC), and manage data lineage to track how data flows through your system. Once your data is prepared, you’ll move into the analytics layer—learning how to create Gold tables that are structured for business use.

You’ll use SQL Endpoints to run analytical queries and understand how to optimize them for performance. Finally, you’ll connect everything to BI tools like Power BI and Tableau, creating dashboard-ready data and building visualizations that drive real business decisions. What Makes This Course Unique?

This is not just another tutorial-based course.

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Duration: Self-paced

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Databricks for Data Engineers: Full Curriculum (Structured)

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