Courses @ UNIRAZAK

Predictive Analytics

Credit

3

Level of Study

Bachelor Degree

Synopsis

This paper covers the basics of predictive data analytics, statistical computing and visualisation. Students develop an understanding of data science, from the basic skills of data processing and visualisation to building sophisticated descriptive and predictive models.This paper focuses on developing models for classification and prediction. The aim is to use a set of predictor variables to model the outcome of a target variable using techniques such as least squares and logistic regression, k-nearest neighbours, classification and regression trees (CART), and hierarchical classifiers. Shrinkage-based methods for model selection and cross-validation for model evaluation are also introduced.

Learning Outcomes

  • Apply classification and prediction modelling techniques to turn data into actionable insights.
  • Perform model selection to identify the most important predictors out of a potentially very large set of predictor variables.
  • Explain the importance of reproducible reporting and report on the results of a statistical analysis of a data set.
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