MessageRelay Digital Academy

Data · Foundations

Pipeline Foundations with Python

Build batch ingestion jobs, version control lab artifacts, and document lineage for your first portfolio pipeline.

This cohort walks you through designing a reproducible batch pipeline from raw CSV drops to curated tables. You will configure virtual environments, write idempotent extract scripts, and pair with a mentor on code review twice per week. Labs mirror scenarios common in Daejeon SaaS teams: nightly syncs, schema drift handling, and observability hooks. Expect 8–10 hours weekly including live critique sessions.

₩890,000 · 8 weeks · Blended

Request information Refund & Cancellation
Abstract visualization of data streams on multiple monitors

Included in this cohort

  • Python 3.12 lab environment with pre-built datasets
  • Git-based submission workflow with rubric feedback
  • Lineage diagram template for portfolio use
  • Two mentor code reviews per module
  • Slack office hours in KST evenings
  • Capstone: ingest + transform + export to Parquet
  • Peer review rotation on documentation quality

Outcomes you can show

  1. Ship a documented batch pipeline with tests
  2. Explain schema evolution strategies in interviews
  3. Present a 5-minute architecture walkthrough
Portrait of Min-jun Park

Mentor

Min-jun Park

Former platform engineer; seven years building ingestion services for logistics APIs.

Common questions

No. We start with Python and SQL. Spark appears in later programs. Basic scripting comfort is enough.

Learner notes

"The Pipeline Foundations capstone gave me a repeatable checklist for staging tables. Mentor notes on my dedupe logic were sharper than any tutorial I tried."

Hyeon-woo · Junior analyst

"Week 4 felt dense, but the office-hour recording helped. I reused the lineage template in a freelance gig."