Python Programming Course: Level 1B

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

COVID-19 update: arrangement of our courses

We are now delivering courses online and in-person. Please check the delivery format of each class before enrolling.

Please note that course materials (excluding prescribed texts) are shared electronically within 48 hours of course commencement. Printing is not available.

The ability to extract useful insights from big data is one of the most highly-valued skills in today’s knowledge economy. Python’s massive library of functions makes it easy to examine, filter, transform and visualise datasets in ways not possible with spreadsheets or relational databases. With the availability of user-friendly development environments such as Jupyter Notebook, it’s easier than ever to get started.

This course is part two of a two-part Introduction to Python series. 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

In this course, you will build on the fundamental Python programming skills acquired in the Python Programming Course: Level 1A and learn to apply them to contemporary data analysis tasks, including social media analytics, text analytics and data visualisation.

Outcomes

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

• import and export data
• work with Pandas series and dataframes
• query data in an external database
• perform descriptive and predictive analyses
• analyse text
• create basic graphs and visualisations.

Content

• Reading from and writing to data files
• Understanding, creating and using Pandas series and dataframes
• Data cleaning, indexing, querying, sorting, aggregating and merging
• Database access and queries
• Descriptive and predictive data analysis
• Text cleaning and analysis
• Data visualisation

Intended audience

Suitable for professionals, students and academics who want to develop more advanced Python skills and get a taste of Python’s extensive data analysis and visualisation capabilities.

Prerequisites

It is assumed you have computer and data literacy knowledge to the level of performing basic data analysis tasks, ie, high school algebra, percentages, probability, averages. It is assumed you have completed Python: Level 1A or have equivalent knowledge.

Delivery style

Modes of delivery

• Face-to-face, presenter-taught training using your own device
• Online training via the platform Zoom

Face-to-face classes

These classes run in a classroom and you need to bring your own device with Anaconda Python installed. You should ensure it is fully charged as access to power is limited.

Please note that the University does not carry any responsibility for your lost, stolen, or damaged devices whilst on the University premises.

Online classes

If you are attending an online class, you will need your own device with Anaconda Python installed.

Materials

Training materials, including a mixture of step-by-step instructions, examples and exercises are provided electronically. These materials will serve as a useful reference when working with Python in future.

Before the course

Anaconda Python Version 3.x of is required and can be downloaded free of charge from Anaconda.