Python for Non-Computing Students

Course Overview

This 10-week course is designed for students from non-computing backgrounds (Accounting, Finance, Physics, Biology, Chemistry) who want to gain practical data analysis skills. You’ll learn Python fundamentals with a focus on CSV/Excel handling, numerical computation, visualization, and automation.

What you’ll gain

Practical Python skills for data analysis
Ability to clean, visualise and export data
Automation of weekly/monthly reports
A capstone project relevant to your discipline

Weekly Breakdown

Week 1 — Python Basics & Problem Solving

Topics: Why Python, environment setup, variables, operations, conditionals. Examples: discounts & interest (Accounting), unit conversions (Physics), formula evaluation.

Week 2 — Data Structures & File Basics

Topics: Lists, loops, dicts, tuples/sets, functions. Examples: expense trackers, experiment data storage, inventory/grades.

Week 3 — Functions & NumPy

Topics: NumPy arrays, array ops, math functions, basic file I/O, intro to CSV.

Week 4 — Data Visualization

Topics: Visualization principles, Matplotlib basics, plot customization.

Week 5 — Advanced NumPy

Topics: Multi-dimensional arrays, matrix operations, curve fitting, NumPy file I/O.

Week 6 — Pandas I

Topics: Series & DataFrames, CSV/Excel handling, basic operations.

Week 7 — Pandas II

Topics: Data cleaning, filtering, aggregation, exporting.

Week 8 — Advanced Visualization

Topics: Seaborn, advanced plots, multi-plot figures for presentations.

Week 9 — File Automation

Topics: Batch file processing, integration, error handling, project planning.

Week 10 — Final Project (Capstone)

Focus: Build a capstone (financial tool, analysis system, or interactive dashboard) and present your deliverable.

Sample Use-Cases

Accounting: Financial dashboards
Finance: Forecasting & automation
Physics: Experimental data pipelines
Biology: Lab data processing
General: Report automation

Resources

Slides provided.

These will be added as the weeks happen