Type of Course: Upskilling
Data analytics examines organisational issues by using available data and a range of analytical techniques to generate meaningful insights. For example, analytics may be used to identify sales trends over time, evaluate customer perceptions of products and competitors, or support evidence-based decision making through statistical and visual analysis.
This course introduces participants of all experience levels to the R programming language using the open-source R Studio environment. In a single two-hour session, you will learn what R is, how to install and configure it, and be introduced to core programming concepts, including importing data, writing simple code, and generating basic analytical outputs such as tables and charts.
The session is designed for beginners and provides an accessible introduction to working in a programming analytical environment. Alongside learning the fundamentals of R programming, participants will also explore how modern Artificial Intelligence (AI) tools can support the coding process. This includes using AI to help explain code, troubleshoot errors, suggest programming approaches, and accelerate learning while still developing a clear understanding of the underlying analytical techniques.
As RStudio is free and open source, participants may install it on their own devices provided they have administrator rights. Following this introductory session, participants may choose to continue onto the wider Data Analytics Series, consisting of eight structured two-hour lectures covering topics such as data visualisation, tables and charts, data distributions, hypothesis and pattern testing, and an introduction to machine learning.
Note: If you are unsure whether working within a programming analytical environment is right for you, this introductory session provides an ideal opportunity to explore the experience before committing to further study. If you would like additional information before enrolling, please contact the email address below.
Pre-requisites for joining:
• No prior programming experience is required, but you would like to try it.
• A willingness to learn analytical thinking and problem-solving in a programming environment
• An interest in developing practical skills in data analytics and AI-assisted programming workflows
