Data analytics addresses organisational challenges by utilising existing data and applying various techniques to generate actionable insights. For example, it can be applied to analyse trends in sales over time or assess customer perceptions of products or competitors using appropriate analytical methods. This course uses the open-source R Studio package and is structed across three levels.
It begins with a single 3 hour session Data analytics addresses organisational challenges by utilising existing data and applying various techniques to generate actionable insights. For example, it can be applied to analyse trends in sales over time or assess customer perceptions of products or competitors using appropriate analytical methods.
This course uses the open-source R Studio package and is structured across three levels. It begins with a single 3 hour session, designed to allow participants to determine if they wish to pursue the full course. The introduction covers the basics of R and demonstrates how to create and execute simple R scripts. If participants choose to continue, a series of additional 2 hour sessions explore data analysis within the R environment, introducing data structures, and demonstrating the creation of tables and charts relevant to decision-making problems. Basic hypothesis testing, correlation, and regression modelling are also covered.
For those interested in further study, an additional module on machine learning is available. This module introduces algorithms such as logistic regression, decision trees, artificial neural networks, and isotrees; and don’t be concerned about the mathematics of these algorithms, the computer handles the complexity, you just need to concern yourself with interpreting its output.
