Course overview
In this course students develop skills for taming real-world data into forms that allow it to be used, and then apply this cleaned data in predictive models. Students will gain skills in tidy data, types of data and data formats, exploratory data analysis, data transformation, as well as model fitting and prediction using statistical machine learning tools. This course broadens the tools students will have experience with and helps to develop critical thinking skills and problem solving.
Course learning outcomes
- Describe the principles of data taming and approaches used to tidy data
- Identify the different types of data and data variables
- Select from data analysis and visualisation techniques to create a predictive model and make predictions from it
- Execute techniques to transform, reduce and summarise data in order to visualise it
- Communicate professionally on the application of predictive models through the use of real-world case studies
Degree list
The following degrees include this course