Data · Beginner
Python for Data Pipelines
Learn to ingest, clean, and transform data using Python tooling common in Korean tech teams. Build pipelines that mentors evaluate for readability and error recovery.
Features
- pandas and polars comparisons
- Apache Airflow basics
- Data quality checks
- Parquet and CSV ingestion patterns
- Logging and retry strategies
- Visualization handoff to BI tools
Outcomes
- Documented ETL pipeline with sample data
- Data dictionary for capstone dataset
- Mentor-signed completion checklist
Ji-hoon Lee
Data engineer; previously built pipelines for manufacturing analytics.
FAQ
High-school statistics is enough; we focus on practical coding.
Reviews
"Week 4 quality checks changed how our team validates CSV uploads."