# Data Analysis with Python

> Learn Python from the ground up to clean, analyse and visualise data, no programming background required.

- **Provider:** Afriskora Training Solutions
- **Category:** Data, AI & Digital Skills
- **Duration:** 5 days
- **Formats:** classroom (cities across Africa), live virtual (Zoom/Teams), in-house for teams
- **Certificate:** Afriskora Certificate of Completion, verifiable online
- **Booking:** request dates and a quote; invoice and EFT payment
- **Web page:** https://afriskora.co.za/courses/data-ai-digital/data-analysis-with-python
- **Request dates:** https://afriskora.co.za/request-training?course=data-analysis-with-python

## Overview

Python is the most widely used language for data work. This course takes participants from their first line of code to analysing real datasets with pandas and presenting results with charts. Every session is hands-on, using examples from finance, operations and public-sector reporting, so participants can automate repetitive spreadsheet work and answer questions with data.

## Who should attend

- Analysts and officers who work in Excel
- Researchers and M&E professionals
- Finance and operations staff
- Anyone starting a career in data

## Learning outcomes

- Write Python code to load, clean and transform data
- Use pandas to summarise, group and join datasets
- Create clear charts with matplotlib and seaborn
- Automate repetitive reporting tasks
- Present findings that support decisions

## Course outline

### Day 1: Python foundations

- Setting up Python and Jupyter
- Variables, data types and lists
- Loops, conditions and functions
- Reading files

### Day 2: Working with data in pandas

- DataFrames and Series
- Importing Excel and CSV data
- Selecting and filtering
- Handling missing values

### Day 3: Analysis techniques

- Grouping and aggregation
- Merging datasets
- Dates and time series
- Descriptive statistics

### Day 4: Visualising data

- Charts with matplotlib
- Statistical plots with seaborn
- Choosing the right chart
- Formatting for reports

### Day 5: Automation and project

- Automating a monthly report
- Exporting results to Excel
- Good coding habits
- Capstone analysis project