Image unavailable
6 weeks · cohort · intermediate
Data Pipelines in Python Pandas-heavy weeks alternate with orchestration concepts. You wire retries, schema checks, and lightweight data quality gates suitable for teams without a full data engineering bench.
JPY 92,000
Informational price — no checkout here. See Returns & Refunds .
Request information
What the syllabus includes Ingest patterns for CSV, parquet, and bounded API pulls Pandas idioms that survive memory pressure on laptops Great Expectations-style checks simplified for small teams Slack/email alerts on failure with redacted samples Containerized runner stub (Dockerfile included) Lineage notes in Markdown for audit trails Partner lab with career coach on how to describe pipelines in interviews Outcomes you can demonstrate Publish a documented pipeline README non-engineers understand Instrument failures without drowning in noise Choose batch vs incremental with a written decision log Mentor of record Image unavailable
Amelia Costa
Backend mentor — built ingestion for climate sensor networks.
FAQ Spark or Kafka? Out of scope; we focus on single-node Python stacks that many SMEs actually run.
Experience notes Quality gate snippet from Data Pipelines in Python went straight into our finance close process.
Mentor feedback on my README was blunt—in a useful way. Still tweaking week four notebook.
— Lin , Analyst · Manufacturing · Trustpilot 