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Structured learning draft

Python for AI & Data Science

Turn untidy data into a defensible finding. You will finish with a cleaned dataset, analysis and decision-ready chart.

Start first lessonDownload A4 workbook (PDF)Preview guideFormative knowledge check

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Data & PythonTool stack
Pythonpandas
Technology marks for Python for AI & Data Science, sourced from the CC0-licensed Simple Icons project.
12guided lessons
4focused modules
1reviewable project
PDFoffline workbook

The problem

What this course helps you do

Python for AI & Data Science is a structured, practical course covering Python, NumPy, Pandas, Matplotlib. It emphasizes explainable methods, checked work and a final outcome that can be reviewed.

Who it is for

Learners using data and code to answer practical questions.

Prerequisites

  • Basic numeracy and file-management skills

Portfolio-ready project

Produce a reviewable Python for AI & Data Science project using Python, NumPy, Pandas.

Deliverable: A working Python for AI & Data Science artefact plus an evidence-based self-review.

Practice fileAnalysis practice datasetFictional monthly service data with units and dates.Planning template · MarkdownProject briefDefine the user, outcome, boundaries, evidence and acceptance criteria before building.Printable workbook · PDFComplete course workbookA4-ready lesson prompts, project worksheets, evidence logs and references.

Downloads open without an account. Practice data is fictional; review each file before using it in another system.

Definition of done
  • The output matches the stated outcome.
  • Inputs and decisions are reproducible.
  • Boundary and failure evidence is included.
  • Limitations and responsibility considerations are explicit.

Course plan

From first concept to finished work

Source-led learning

Authoritative references

Course claims are grounded in primary documentation and recognized public guidance. Recheck version-sensitive information before professional use.