Modern Data Engineering with SQL and Python

Entry requirements

F01; basic relational data concepts

What 36 hours means

Lessons

24 h

Capstone

8 h

Assessment

2 h

Remediation

2 h

Syllabus

Four modules, twelve lessons. Every lesson states what it covers and the evidence you produce for it.

• Module

  01

  3 lessons · 6 h

  

  Module 1

  Data modelling

  Relational modelling · SQL selection and joins · Aggregations and windows

  D01Show lessonsHide lessons▾

  1. D01.01 · 120 min

     Relational modelling

     Model customers, orders and events with keys and cardinalities.

     Evidence: A schema that prevents orphan orders and represents repeated events.

  2. D01.02 · 120 min

     SQL selection and joins

     Query related tables while controlling duplicate row multiplication.

     Evidence: Expected row counts and totals match fixture answers.

  3. D01.03 · 120 min

     Aggregations and windows

• Module

  02

  3 lessons · 6 h

  

  Module 2

  Ingestion

  Files and schemas · API ingestion · Batch and event ingestion

  D01Show lessonsHide lessons▾

  1. D01.04 · 120 min

     Files and schemas

     Read CSV, JSON and columnar files; validate expected fields.

     Evidence:

• Module

  03

  3 lessons · 6 h

  

  Module 3

  Transformation

  Transformation design · Data quality · Orchestration

  D01Show lessonsHide lessons▾

  1. D01.07 · 120 min

     Transformation design

     Separate raw, cleaned and serving datasets with traceable changes.

     Evidence:

• Module

  04

  3 lessons · 6 h

  

  Module 4

  Operations

  Backfills and recovery · Performance and cost · Pipeline documentation

  D01Show lessonsHide lessons▾

  1. D01.10 · 120 min

     Backfills and recovery

     Reprocess an earlier interval without corrupting current data.

     Evidence:

Capstone

Build a reliable ingestion pipeline for synthetic orders and delivery events, with incremental loads, quality checks and a documented recovery procedure.

Lab environment

Data sandbox

Lab infrastructure is not yet provisioned, so this describes the environment the course is designed for rather than one you can launch today.

Part of a pathway

• Data Engineering Professional