CSC-30043 - Module Specification
School of Computer Science and Mathematics
Faculty of Natural Sciences

Programme/Approved Electives for 2024/25

Available as a Free Standing Elective

Co-requisites

None

Prerequisites

CSC-10058 Introduction to Data Science I
CSC-10060 Introduction to Data Science II

Barred Combinations

None

Description for 2024/25

As the capacity to store large amounts of data as well as the capacity to process such data increases exponentially the need for data mining expertise is paramount. Many companies have been harvesting data from their operations for many years and are realising the amazing potential that this data can unlock in terms of informing their future operations. Maximising efficiencies, sales potentials and cutting down costs are among the many benefits that can be gained by the data mining knowledge and skillset that this module will provide.

To provide the full skillset that is required from a data scientist in order to identify and collect appropriate data sets (sampling, selection etc.), pre-processing methods (cleaning, filtering etc.) and subsequently apply techniques in order to generate new information.

Intended Learning Outcomes

Identify and collect appropriate data in order to design a data mining work flow.: 1
Apply pre-processing techniques to the collected data sets that minimise bias and distortion in the data.: 1
Select and apply appropriate data mining techniques in order to extract new and useful information from the data.: 1
Validate the findings of a data analysis and quantify their validity.: 1

Study hours

Lectures: 20h
Group work and preparation for presentation: 50h
Independent study: 80h

School Rules

None

Description of Module Assessment