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PythonIntermediate
Python Applied
Data Processing and Analytics
28 hours114 lessons Self-study
EE
Emmanuel Edegbo
Lead Data Engineer & Architect
About this course
Use pandas, NumPy, and matplotlib to clean, transform, analyse, and visualise real-world datasets.
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
114
Lessons
28h
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 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
- ✓Load, clean, and transform data with pandas DataFrames
- ✓Perform numerical operations with NumPy arrays
- ✓Create visualisations with matplotlib and seaborn
- ✓Handle missing data, duplicates, and data type conversions
- ✓Merge, group, and pivot datasets for analysis
- ✓Complete a data analytics project with pandas
Who this is for
Software testersBusiness analystsData analystsData engineersCyber security professionalsData scientists
Curriculum
114 lessons · 27h 36m1. From Core to Applied5 lessons
2. NumPy Foundations11 lessons
3. Pandas: DataFrames & Series9 lessons
4. Filtering, Sorting & Aggregation10 lessons
5. Reshaping & Combining Data8 lessons
6. Data Cleaning10 lessons
7. Excel, JSON & XML9 lessons
8. Dates, Times & Time Series9 lessons
9. HTTP APIs & Web Data9 lessons
10. Database Connectivity9 lessons
11. Data Visualisation10 lessons
12. Production Pipelines12 lessons
13. Capstone Project — EnergyPY Applied: Quarterly Billing Pipeline2 lessons
14. Python Applied Cheat Sheet1 lessons
Prerequisites
- •Python Core or equivalent Python foundation
Better Together · Python Applied
Pair this course with the Python Applied portfolio
The Python Appliedportfolio 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 Applied Portfolio TrilogyTrilogy SKU
From £369.00 — 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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