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Databricks Core

Foundations for Lakehouse Engineering

8 hours22 lessons Self-study
EE
Emmanuel Edegbo

Lead Data Engineer & Architect

About this course

Understand the lakehouse paradigm, Unity Catalog, Spark fundamentals, and medallion architecture on Databricks.

Datasets used

SalesPYRetail dataset loaded as Delta tables for transformation and aggregation work.
FinancePYCompliance dataset for monitoring and aggregation pipelines on the Lakehouse.

Tools you'll need

  • Databricks Community Edition or paid workspace
  • PySpark
  • SQL

What you get when you enrol

  • Lifetime access to every lesson, exercise, and update — including future revisions to this course.
  • 12-month Azure SQL practice access against the same datasets used in the course (read-only). Renews on request for active learners.
  • Auto-graded labs in your browser — write SQL, hit Run, get instant feedback against the expected result.
  • AI-graded Professional Challenges — open-ended scenarios reviewed against a published rubric, not just a single right answer.
  • Course discussion + community — talk to other learners and ask the instructor questions inside the course.
  • Basic Certificate on demonstrated capability — awarded when you complete every Hands-On Lab and Module Readiness Check, plus the Professional Challenges. Confirms you can write, run, and defend course-level SQL against real datasets.
  • Optional Advanced Certificate on completion of SQL Core multi-project— a separate credential awarded when you complete all three capstone projects, each independently assessed and approved by an instructor. Each project is end-to-end query engineering against a real brief with defined acceptance criteria — proves competence at a level an employer can actually evaluate. The Basic Certificate alone confirms course mastery; the Advanced Certificate confirms you can deliver.
  • Optional live training upgrade — instructor-led cohort sessions with capped capacity, sold separately.

What you'll learn

  • Understand the lakehouse architecture and Delta Lake
  • Navigate Databricks workspace, notebooks, and clusters
  • Write Spark SQL and PySpark for data exploration
  • Implement medallion architecture (Landing → Bronze → Silver → Gold)
  • Use Unity Catalog for data governance
  • Complete a lakehouse foundations project

Who this is for

Software testersBusiness analystsData analystsData engineersRecruitersData scientists

Prerequisites

  • SQL Applied and Python Core recommended

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