Module Descriptor School of Computer Science and Statistics
|Module Name||DATA ANALYTICS|
|Module Short Title|
4 lectures and 1 lab per week.
|Module Personnel||Dr Bahman Honari|
To understand the theory and be able to apply the following techniques to a set of data
The aim of the course is to introduce the students to a set of techniques including classification and regression trees, and ensemble methods. Methods to evaluate models will also be discussed.
|Recommended Reading List|
A course on Multivariate Analysis covering principal components multiple regression, clustering techniques and logistic regression. A good working knowledge of R is also required.
Students will be required to carry out a project worth 40% of the total marks with an exam in the n accounting for the remaining 60%.
Assessment in the Supplemental session will be based on 100% exam.
|Academic Year of Data||2018/19|