Introduction to Python Course: Level 1B

Data Analysis and Analytics. Uncover insights and transform your organisation.

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 and Spyder, 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.

Aims

This course aims to teach data analytics and visualisation skills using Python.

Outcomes

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

• use object-oriented functions
• access data in an external database
• perform predictive analytics using linear and logistic regression
• segment data using cluster analysis
• analyse text using regular expressions
• produce data visualisations.

Content

This course covers the following topics:

• Object-oriented programming
• Numpy arrays
• Database access
• Predictive analytics
• Dimension reduction
• Cluster analysis
• Data visualisation
• Text analytics using regular expressions
• Integration with Tableau Desktop visualisation software.

Intended Audience

This course is suitable for professionals and academics who want to develop more advanced Python skills.

Prerequisites

It is assumed you have completed the Python: Level 1A course or equivalent.

Delivery Style

• Workshop
• Computer based training on your own device

Materials

You will be provided with a workbook including a mixture of step-by-step instructions and exercises. The workbook 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 Python is installed on your device before class. Version 3.x is required and can be downloaded from Anaconda.