| CODE | IFC3000 | ||||||
| TITLE | Dissertation | ||||||
| 今日黑料 LEVEL | 03 - Years 2, 3, 4 in Modular Undergraduate Course | ||||||
| EQF/MQF LEVEL | 6 | ||||||
| ECTS CREDITS | 20 | ||||||
| DEPARTMENT | Faculty of Science | ||||||
| DESCRIPTION | Students pursuing the degree in Computational Statistics and AI will write a dissertation on a topic selected from a range of themes proposed by staff from the Department of Artificial Intelligence, the Department of Computer Information Systems or the Department of Statistics and Operations Research. Topics will reflect the research areas and expertise of the academic staff from these departments. Study-unit Aims: This study-unit is designed for students of the BSc in Computational Statistics and AI degree, offering an in-depth exploration of advanced topics in artificial intelligence, computing science or statistics. Students will delve deep into theoretical concepts and practical applications, with a focus on conducting independent research that integrates key elements of these disciplines. The project facilitates the application of theoretical knowledge to real-world scenarios, allowing students to demonstrate the practical implications of their research. It is meant to showcase their ability to conduct independent research, critically analyze complex issues within various sectors, and to communicate their findings effectively. It also enhances written and oral communication skills, guiding students in effectively articulating their research findings, methodologies, and conclusions in the form of a comprehensive dissertation. Learning Outcomes: 1. Knowledge & Understanding By the end of the study-unit the student will be able to: - define a clear and well-motivated research question in the areas of artificial intelligence, computing science, or statistics; - develop in-depth understanding and expertise in a chosen specialist topic within these fields; - use theoretical concepts to address practical problems, including, where appropriate, the analysis of real-world data. 2. Skills By the end of the study-unit the student will be able to: - critically evaluate existing models, methods, and industry practices to gain a clear understanding of their capabilities and limitations; - communicate research outcomes effectively by presenting methods, results, and conclusions in a clear and well-structured way; - undertake independent research, including literature review, data gathering, and analysis, culminating in a written dissertation; - develop skills and experience that support future academic research and professional practice in AI, computing science or statistics. |
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| STUDY-UNIT TYPE | Dissertation | ||||||
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2026/7. It may be subject to change in subsequent years. |
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