Standalone CPD Modules

This module empowers professionals from non-STEM backgrounds to confidently engage with data science in their work. Designed specifically for those who are new to quantitative methods, the module takes an intuitive, accessible approach to the technical language commonly used for data science and analytics. Rather than diving into creating complex mathematics, the module focuses on interpretation—teaching participants how to confidently read, run, and extract insights from existing dashboards and reports, written in R and Python.

The objective of the module is to equip students with an understanding of how data engineering principles make data accessible to a wide range of users so they can make informed decisions and optimize their organization's performance. Concepts such as the data lifecycle, data platforms, data collection and storage, data processing and reporting, data analysis and visualisation, ethics, security and governance will be introduced and explored.

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The objective of the module is to equip students with the skills necessary to undertake project work as a data scientist. Project planning, reviewing existing methodologies and the presentation of outputs in different forms all form part of this. This module will also include ethical considerations of data usage.

This module introduces professionals to the critical role of environmental data in addressing global sustainability challenges. Designed to be accessible to those without prior analytics experience, it demystifies the diverse datasets used in climate science, ecology, and geospatial analysis. Rather than focusing on complex technical processing, the module empowers students to critically interpret environmental data, understand its inherent limitations, and use it to confidently inform sustainable decision-making in various organisational contexts.