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PythonAdvanced

Python Professional

Production Data Engineering

34 hours117 lessons Self-study
4.7 (31)
EE
Emmanuel Edegbo

Lead Data Engineer & Architect

About this course

Build production-grade data pipelines, REST APIs, unit testing frameworks, and deployment-ready Python applications.

Python has become the dominant language in data analytics, engineering and science — approachable enough to learn quickly, powerful enough to use in production. SQL handles structured queries; Python handles everything around them.

Course at a glance

14
Chapters
117
Lessons
34h
Estimated time
Self-study
Format

Datasets used

SalesPYRetail dataset for sales analysis, revenue computation, and customer segmentation work.
FinancePYBanking dataset for transaction monitoring, risk classification, and compliance reconciliation work.

Tools you'll need

  • Python 3.12+
  • VS Code with Python + Pylance extensions
  • Virtual environments (venv)
  • Git

What you get when you enrol

  • Lifetime access to every lesson, exercise, and update — including future revisions to this course.
  • 12-month Azure SQL practice access against the same datasets used in the course (read-only). Renews on request for active learners.
  • Auto-graded labs in your browser — write SQL, hit Run, get instant feedback against the expected result.
  • AI-graded Professional Challenges — open-ended scenarios reviewed against a published rubric, not just a single right answer.
  • Course discussion + community — talk to other learners and ask the instructor questions inside the course.
  • Basic Certificate on demonstrated capability — awarded when you complete every Hands-On Lab and Module Readiness Check, plus the Professional Challenges. Confirms you can write, run, and defend course-level SQL against real datasets.
  • Optional Advanced Certificate on completion of SQL Core multi-project— a separate credential awarded when you complete all three capstone projects, each independently assessed and approved by an instructor. Each project is end-to-end query engineering against a real brief with defined acceptance criteria — proves competence at a level an employer can actually evaluate. The Basic Certificate alone confirms course mastery; the Advanced Certificate confirms you can deliver.
  • Optional live training upgrade — instructor-led cohort sessions with capped capacity, sold separately.

What you'll learn

  • Build production data pipelines with error handling and logging
  • Create REST APIs with FastAPI or Flask
  • Write unit tests with pytest and implement CI/CD patterns
  • Work with databases using SQLAlchemy ORM
  • Package and deploy Python applications
  • Complete a production data engineering project

Who this is for

Software testersData engineersData scientists

Curriculum

117 lessons · 33h 56m
1. From Applied to Professional5 lessons
2. OOP Design Patterns10 lessons
3. Decorators & Context Managers10 lessons
4. Generators & Iterators10 lessons
5. The Type System11 lessons
6. Async I/O9 lessons
7. Multiprocessing & Concurrency9 lessons
8. Packaging & Dependency Management11 lessons
9. CLI Tools & Configuration9 lessons
10. Docker & Containerisation9 lessons
11. CI/CD Pipelines11 lessons
12. Production Patterns10 lessons
13. Capstone Project — EnergyPY Professional: Production Billing Service2 lessons
14. Python Professional Cheat Sheet1 lessons

Prerequisites

  • Python Applied or strong intermediate Python skills
Better Together · Python Professional

Pair this course with the Python Professional portfolio

The Python Professionalportfolio mirrors this course level — once you've worked through the lessons, the projects give you a graded, instructor-reviewed deliverable on the same stack and a LinkedIn-ready summary on completion.

Python Pro Portfolio TrilogyTrilogy SKU
From £599.00 — paired with this course saves an additional 15% on standalone add-ons.

3 sector standalones available — pick one or the full trilogy.

What learners say

How ratings work
4.7
31 ratings (time-weighted)
  1. 5
    22
  2. 4
    9
  3. 3
    0
  4. 2
    0
  5. 1
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