Programme/Approved Electives for 2024/25
None
Available as a Free Standing Elective
No
CSC-10058 Introduction to Data Science ICSC-10060 Introduction to Data Science II
Aims
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.: 1Apply pre-processing techniques to the collected data sets that minimise bias and distortion in the data.: 1Select and apply appropriate data mining techniques in order to extract new and useful information from the data.: 1Validate the findings of a data analysis and quantify their validity.: 1
Lectures: 20hGroup work and preparation for presentation: 50hIndependent study: 80h
Description of Module Assessment
1: Group Project weighted 100%Group Project based on solutions to external partners' data related problemsExternal partners to the school/university (such as companies, services, government bodies etc.) will be invited to present data-related problems to which groups of students (maximum of 5 students in each) will attempt to address. Real data from such partners will be analysed by applying the data mining techniques that will be learned. Each group will then present their solution in a 20 minute presentation to the problem providers at the end of the module. This will include presentation of data collection, work flow, techniques used and reflection on bias and distortion and the validity of the results. The mark for each student in a group will be composed of a group element as well as an individual element. The former will be the same for all members of the group and the latter will be a result of an individual report (2000 words) that will include the contribution of the student to the group work.