MODULE 2 OF 8 · 30 Hrs · 3 Weeks

Python Programming

Python is the language every data science workflow runs on. This module builds real programming fluency — syntax, data structures and the NumPy/Pandas libraries — before any statistical modelling is introduced.

Who This Module Is For

Students who have completed the mathematics module and are ready to build real, working Python code.

Real-World Relevance

Pandas and NumPy fluency is assumed in almost every data analyst and data scientist job description — this module is the coding foundation the rest of the program is built on.

Program Overview View Hands-On Labs

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Curriculum

What You Will Learn

A detailed, industry-aligned breakdown of every topic covered in this module.

Python syntax, data types & control flow
Functions, modules & OOP basics
Lists, dictionaries, tuples & sets
File handling & exception handling
NumPy for numerical computing
Pandas for data manipulation
Working with virtual environments
Writing clean, reusable Python code

Technology Stack

Tools You Will Use

Hands-on time with the same tools used by working data analysts and data scientists today.

Python

Core programming language used across every module, from statistics to machine learning.

Jupyter Notebook

Interactive notebook environment used for data exploration, analysis and model prototyping.

NumPy

Numerical computing library used for array operations and mathematical computation in data science.

Pandas

Data manipulation library used to clean, transform and analyse structured datasets.

VS Code

Primary code editor used for writing, debugging and testing Python and data science code.

Practical Work

Hands-On Labs

Production-style data science lab scenarios, built using real, messy datasets.

Write Python programs using core data structures, functions and control flow.

Manipulate and clean tabular data using Pandas DataFrames.

Perform numerical computations on arrays using NumPy.

Handle files and exceptions in a small Python data-processing script.

Set up an isolated virtual environment for a data science project.

Evaluation

Assessment

Knowledge Assessment

Quiz covering Python fundamentals, OOP basics and core NumPy/Pandas operations.

Practical Evaluation

Students must write a Python script that loads, cleans and summarises a real dataset using Pandas and NumPy.

Portfolio

Projects

Industry-style deliverables added directly to your project portfolio.

Portfolio Project 01

Python Data Processing Script

Build a Python script that loads, cleans and summarises a real-world dataset using NumPy and Pandas.

Module Outcome

What This Module Builds

Students gain solid programming fluency in Python, the core language used throughout data science and machine learning.

Maps to job roles

Python Developer (Trainee)Data Analyst (Junior)Junior Data EngineerData Science Associate — foundation track