| CODE | ARI3000 | ||||||||||||||||
| TITLE | Individual Assigned Practical Task for AI in Statistics and Operations Research | ||||||||||||||||
| 今日黑料 LEVEL | 03 - Years 2, 3, 4 in Modular Undergraduate Course | ||||||||||||||||
| EQF/MQF LEVEL | 6 | ||||||||||||||||
| ECTS CREDITS | 4 | ||||||||||||||||
| DEPARTMENT | Artificial Intelligence | ||||||||||||||||
| DESCRIPTION | The Individual Assigned Practical Task (APT) study unit provides students with the opportunity to work independently on a substantial practical project involving the application of Artificial Intelligence techniques within the fields of Statistics and Operations Research. Each student is required to address all phases of the project lifecycle, including problem understanding and specification, methodological design, investigation of appropriate statistical, optimisation, and AI-based approaches, implementation of computational solutions, and evaluation and testing of results. Project titles, reflecting real-world data-driven and analytical problems, are proposed by the lecturers, with students expected to demonstrate sound judgement in selecting appropriate methods and technologies. A limited number of tutorials are provided, during which the proposing lecturer presents the problem context and offers guidance as required, while the primary emphasis remains on independent, supervised work. Study-unit Aims: The primary aim of this study-unit is to enable each student to independently undertake a real-life, data-driven problem and develop a complete solution through the application of Artificial Intelligence techniques within Statistics and Operations Research. Students are expected to research and evaluate alternative methodological approaches, identify an appropriate and feasible solution, and implement and test this solution using suitable computational tools. Through individual work, the study-unit aims to strengthen students’ problem-solving, analytical reasoning, and programming skills. Students are also expected to document the full project lifecycle in a structured technical report, including problem formulation, review of similar systems, solution design, explanation of the AI techniques employed, implementation details, testing methodology, analysis of results, and conclusions. This study unit further serves as preparation for undertaking an independent Final Year Project. Learning Outcomes: 1. Knowledge & Understanding By the end of the study-unit the student will be able to: - Analyse a given real-world problem scenario and identify appropriate Artificial Intelligence techniques applicable within Statistics and/or Operations Research contexts; - Explain the theoretical and methodological rationale for the selection of AI, statistical, and optimisation techniques used to address the problem; - Explain appropriate evaluation frameworks, metrics, and validation approaches relevant to AI-driven solutions in Statistics and Operations Research; - Interpret and explain the results obtained from the evaluation of the proposed solution in relation to the original problem objectives; - Describe and justify the stages of the analytical pipeline — including problem formulation, methodological design, implementation, evaluation, and results analysis — in the form of a structured technical report or research-style document; - Demonstrate understanding of the developed AI-driven solution through the specification and presentation of at least one tangible artefact suitable for demonstration purposes. 2. Skills By the end of the study-unit the student will be able to: - Apply appropriate analytical, computational, and programming tools to independently solve a given problem or challenge, drawing on knowledge and techniques acquired in previous study units; - Research, evaluate, and assimilate new technologies, methodologies, or tools as required to address a specific problem in an effective manner; - Plan and manage individual project work to ensure timely and structured completion in accordance with given requirements and constraints; - Prepare and deliver a clear and effective presentation of the project using appropriate digital tools for demonstration purposes; - Communicate the key technical, analytical, and methodological aspects of the work clearly and coherently to peers, academics, and other professional audiences through oral and visual presentation. Main Text/s and any supplementary readings: Readings are specific to each APT and will be made available when the APT descriptions are announced. |
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| STUDY-UNIT TYPE | Lecture | ||||||||||||||||
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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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