This module advances the study of algorithms and data structures for the business analyst by examining the various techniques, data structures and algorithms that can be used to ensure that the organisation and access of data is as efficient as possible by examining advanced structures and algorithmic techniques.
Multidimensional arrays; graph theory; binary search trees; rotations in trees for optimisations; multi-way search trees and B-Trees; basic concepts and algorithms associated with data mining such as classification, association and cluster analysis.
Present multidimensional list, in particularly 2D list, storing data in 2D list, accessing, retrieving , and calculating data.
Presenting graph collection, multiple graph types, different traversal techniques on graphs, finding shortest path algorithms.
Binary search trees; rotations in trees for optimisations
Presenting Binary search tree (BST) structures, its operations and implementation. Balancing BST, AVL tree, rotation techniques. Applications of tree structure.
Multi-way search trees and B-Trees
Introduction of low order multi way search tree, structure and operations.
Basic concepts and algorithms associated with data mining such as classification, association and cluster analysis.
Introduction to knowledge discovery. Presenting different data mining techniques and algorithms, applying these techniques for analysing different data set.
This module will be taught using 2-hour weekly lectures and 2-hour practical sessions.
The lectures will provide theoretical material which will be underpinned by many coding examples to demonstrate the use of this material. The practical sessions will provide students with supervised practice time in the lab using appropriate exercises
|Module Content & Assessment