Course overview

Build maintainable data pipelines with Python and SQL. Progress from ingestion and transformation to scheduling, quality checks, incremental processing, and operational recovery using a reproducible project.

For experienced developers. Estimated total study time: 36 hours including practice and capstone work; not a claim of recorded video duration.

Learning outline

1. Pipeline architecture and data contracts (4h)
2. Python ingestion and resilient API clients (6h)
3. SQL transformations and analytical modeling (6h)
4. Incremental loads, retries, and idempotency (6h)
5. Orchestration, data quality, and monitoring (6h)
6. Capstone: tested end-to-end data pipeline (8h)

Prerequisites

Working Python and SQL knowledge; Git; command-line familiarity. A local database and Python environment. Use public or synthetic datasets, not confidential production data.

Development status

Draft course plan. Lessons, recordings, downloadable materials, and assessments are not yet uploaded. Tuition is awaiting approval; any cloud or third-party subscription charges are separate.