Python Programming Course 1A: An Introduction

Data analysis and analytics. Uncover insights and transform your organisation.

Python is one of the most in-demand technical skills and one of the easiest programming languages to learn. With a syntax similar to the English language Python is perfect for beginners. It has numerous applications, from website development to big data analytics and visualisation.

This course is part one of a two-part Introduction to Python series. After completing 1A, we encourage you to proceed with Python Programming Course 1B: Data Analytics. We recommend enrolling in both courses to gain entry level skills. Enrolment in both courses is not compulsory.

Please ensure Anaconda Python is installed on your device before class. For further details, see ‘Before the course’.

Aims

This course aims to teach basic programming skills using Python, including data handling, variable types, operations and functions.

Outcomes

By the end of this course, you should be able to:

• install Python and additional libraries
• use Jupyter Notebook to write and run Python code
• import and export data
• work with basic Python data types (string, float, integer, list, etc)
• work with Pandas series and dataframes
• write Python expressions that involve variables, variable assignment, operators and functions
• use conditional and loop functions
• resolve coding errors
• create basic graphs
• clean and manage data
• find and read documentation for Python libraries and function.

Content

This course covers the following topics:

• introduction to programming
• introduction to Python and Jupyter Notebook
• finding, installing and loading Python libraries
• working with variables and lists
• writing expressions
• debugging
• user input
• writing conditional and loop functions
• creating functions
• understanding, creating and using Pandas series and dataframes
• reading and writing files
• producing basic graphs
• data cleaning, indexing, querying, sorting, aggregating and merging
• finding and reading function documentation.

Intended audience

Suitable for professionals and academics who want to learn programming foundations, and/or improve their data management and analysis skills.

Prerequisites

It is assumed you have computer and data literacy knowledge to the level of performing basic data analysis tasks in Excel, i.e., basic (high school) algebra, percentages, probability, averages, line/bar charts. No prior programming experience is required.

Delivery style

• Workshop
• Computer-based training on your own device

Materials

You will be provided with online training materials including a mixture of step-by-step instructions and exercises. These materials will serve as a useful reference when working with Python in future.

Bring your own device

You are required to bring your own device (Windows or Mac). You should ensure your device is fully charged as access to power is limited. Please note that University does not carry any responsibility for your lost, stolen, or damaged devices whilst on the University premises.

Before the course

Please ensure Anaconda Python is installed on your device before class. Version 3.x is required and can be downloaded from Anaconda.