Module Code - Title:
MS6013
-
DISSERTATION IN DATA SCIENCE AND STATISTICAL LEARNING
Year Last Offered:
2025/6
Hours Per Week:
Grading Type:
N
Prerequisite Modules:
Rationale and Purpose of the Module:
The aim of this module is to enable students to research, develop, analyse and present a Master's dissertation on a relevant data science related problem. The project will synthesise key concepts and methods learned in taught modules. It will allow students to further develop their skills and apply their knowledge via independent research in a chosen domain.
Syllabus:
1. Formulate a research idea and research plan, in conjunction with a supervisor, in
a research topic of interest.
2. Conduct a thorough literature review of the current state-of-the-art in the area.
3. Critique the modelling approaches used and research alternatives.
4. Choose an appropriate methodology to implement and discuss why it is suitable
for solving the problem at hand.
5. Implement the methodology and discuss its strengths and limitations, with
minimal input from the supervisor.
6. Organise and present the results in a logical and coherent manner.
Learning Outcomes:
Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)
On completion of this module students will be able to:
1. Conduct a thorough investigation into a topic of interest with relevance to data
science and statistical learning.
2. Work independently to meet agreed project requirements.
3. Demonstrate strong proficiency in data science and statistical learning methods
applied to a real-world problem.
4. Demonstrate an understanding of and ability to critique the strengths and
limitations of the methods implemented.
5. Communicate the key methodologies used, challenges encountered, decisions
made and relevant results in clear and precise language.
Affective (Attitudes and Values)
On completion of this module students will:
1. Develop extensive critical appraisal skills.
2. Defend their research and justify decisions made.
3. Question any data used and identify potential biases.
4. Judge and challenge the limitations of the methodologies and techniques used.
Psychomotor (Physical Skills)
NA
How the Module will be Taught and what will be the Learning Experiences of the Students:
Students will meet regularly with their project supervisor throughout the term. They will be provided with clear guidelines on project deadlines, and project milestones and deliverables. This module will contribute towards graduating MSc students who are knowledgeable (utilising their knowledge and critical thinking to solve real-world problems), responsible (being able to time manage their own project, work within project deadlines and give regular feedback to the supervisor), creative (being able to identify and develop appropriate solutions to the problem at hand), articulate (being able to report technical and non-technical aspects of their project to stakeholders with clear and precise language), collaborative (working with the supervisory team and other students in the cohort), proactive (making active use of data and research to drive improvements and positive change).
Research Findings Incorporated in to the Syllabus (If Relevant):
Prime Texts:
Other Relevant Texts:
Programme(s) in which this Module is Offered:
Semester(s) Module is Offered:
Summer
Module Leader:
Kevin.Burke@ul.ie