Python for Data Cleaning and Wrangling – Level 5 Course

Reliable analysis depends on data that is appropriately structured, checked and prepared. Raw datasets often contain missing values, inconsistent formats, duplicate records, incompatible structures or fields that need to be reshaped before meaningful analysis can begin.

This programme develops the data-wrangling workflow across eight modules. You will begin with cleaning, preprocessing and transformation before moving into merging datasets, visual inspection, automation and more complex data formats such as JSON, XML and text.

The course also includes an applied project that brings the main stages together. The aim is to help you understand how to move from raw information towards an analysis-ready dataset in a structured and repeatable way.

Python is central to the learning because it supports flexible data manipulation and automation. Basic familiarity with Python can help you connect the concepts to practical use, although no formal entry requirements apply.

Who Should Study This Course?

The programme may suit data analysts, business analysts, data-science learners, developers, researchers, IT professionals and others who want a broader Python-based data-preparation workflow.

Free Foundation or Level 5 Programme?

If you are new to the subject, our free Data Wrangling with Python course provides a focused introduction to cleaning, preprocessing and transformation.

This Level 5 programme is the broader route. It extends into merging, visualisation, automation, complex data types and applied project work across eight modules and 450 hours of study.

Related Learning

If you want a stronger focus on the preprocessing stage used before model training, compare our AI Data Preprocessing course. For broader machine-learning context, our beginner's guide to machine learning explains how prepared data feeds into model development.

Frequently Asked Questions

What is Python for data cleaning?

It is the use of Python and its data libraries to identify, correct, transform and organise raw data before analysis or modelling.

How long is this programme?

The estimated study duration is 450 hours. Because the programme is self-paced, the calendar time needed will depend on how many hours you choose to study each week.

Does the course cover missing data and inconsistencies?

Yes. These are addressed within the data-cleaning and preprocessing module.

Will I learn how to merge datasets?

Yes. Module 4 is dedicated to merging and combining information from multiple sources.

Does it include data visualisation?

Yes. Module 5 uses visualisation as a way to inspect patterns, anomalies and wrangling results.

Does it cover automation?

Yes. Module 6 focuses on automating repetitive data-wrangling tasks with Python.

Will I work with JSON or XML?

The complex-data module covers semi-structured and unstructured formats including JSON, XML and text.

Is this an Ofqual-regulated Level 5 qualification?

No regulated status is established for this course. The Level 5, CPD and endorsement descriptions should not be treated as equivalent to Ofqual regulation.

How does it differ from the free course?

The free course is a three-module introduction. This programme is a 450-hour, eight-module route that extends into integration, visualisation, automation, complex data and applied work.