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PythonAdvanced
Python Professional
Production Data Engineering
34 hours117 lessons Self-study
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.
Who this course is for
- ✓Analysts ready to move beyond spreadsheets and SQL into scriptable, repeatable analysis
- ✓Career switchers targeting data analyst, data engineer, or data science roles
- ✓SQL-first professionals who keep hitting problems a query alone can't solve — file wrangling, APIs, automation
- ✓Anyone who wants a programming foundation built around real datasets, not toy exercises
Who this course is NOT for
- ✗Experienced Python developers — Core starts from zero; join at Applied or Professional instead
- ✗Anyone after web development — this track is data-focused (pandas, pipelines, automation), not Django or front-ends
- ✗Learners who only need to query databases — the SQL track covers that faster
How you'll learn
- →Each chapter follows the same rhythm: concept → syntax → worked example → expected output → hands-on lab
- →You write real scripts against the SalesPY and FinancePY datasets from the first chapters — not isolated snippets
- →Auto-graded labs give instant feedback; AI-graded Professional Challenges give rubric-based scores in seconds
- →Module Readiness Checks at the end of every chapter confirm you're solid before moving on
- →Course discussion lets you ask the instructor and other learners questions inline with each lesson
By the end of this course, you'll be able to
- ✓Read, write, and debug Python confidently — functions, data structures, files, and errors
- ✓Wrangle real datasets with pandas: load, clean, transform, aggregate, and export
- ✓Automate repetitive data work end-to-end instead of doing it by hand
- ✓Structure a project with virtual environments and Git like a professional
- ✓Translate a business question into a working, documented Python analysis
Course at a glance
14
Chapters
117
Lessons
34h
Estimated time
Self-study
Format
Datasets used
| SalesPY | Retail dataset for sales analysis, revenue computation, and customer segmentation work. |
| FinancePY | Banking 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 the Python Professional 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 work 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 56m1. 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
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