Learn to build reliable data pipelines, transform raw data into analytics-ready datasets, and deliver dashboards-ready outputs.
Modern Data Engineering is a live, instructor-led program that teaches how real companies move data from sources to usable insights. You’ll learn data modeling basics, batch and streaming pipelines, data quality and governance, and how to build ETL/ELT workflows using industry-standard tools. The program is hands-on—labs, assignments, and a capstone project that proves you can build and maintain production-style pipelines.
Build end-to-end pipelines, learn data quality discipline, and gain the skills to support analytics, BI, and AI workloads.
ETL / ELT Workflows
Hands On Practice
Warehouse Basics
Modern Patterns
Production Discipline
BI Friendly Outputs
Industry Style Pipelines
Learn patterns used in real companies—reliability, scheduling, and monitoring.
Hands On Capstone
Build a full pipeline project that proves end-to-end delivery capability.
Quality Discipline
Learn data validation, testing mindset, and governance basics for production readiness.
Batch, streaming, retries, idempotency, and scheduling—built the right way.
Design analytics-ready tables that make dashboards fast and reliable.
42 Learn is a nice platform for gaining knowledge and working on projects. I have learned a lot about real-time projects and gained knowledge of things I had never learned before. Thank you!
Checks, constraints, validation, and reliability mindset for production pipelines.
Build datasets that power BI dashboards, reports, and AI workloads.
Deliver an end-to-end project: ingest, transform, validate, and publish analytics-ready tables with documentation.
Earn a completion certificate and project review feedback on your capstone.