COMP1961 Essentials of Data Science
COMP1963 Machine Learning with Applications
COMP1964 Data Analytics and Visualisation

The aim of the Level 7 project is to enable students to demonstrate advanced analytical and problem-solving skills by conducting independent, methodologically sound research that addresses a complex, data-driven question. The project should integrate theoretical knowledge with practical application, employ appropriate data science techniques, and produce outcomes that contribute meaningful insights or solutions within the chosen domain.

1. Exercise autonomy and informed judgment to identify and justify a suitable data science project topic, producing a well-structured and critically reasoned proposal.
2. Plan, manage, and implement a complex data science project effectively, demonstrating independence, adaptability, and systematic application of advanced methods under supervisory guidance.
3. Critically evaluate the methods, processes, and outcomes of the project against the project objectives, identifying limitations and proposing evidence-based improvements.
4. Critically apply advanced understanding of ethical principles and risk management throughout the planning, execution, and evaluation phases of the project, ensuring compliance and integrity in data science practice.
5. Communicate effectively the results and findings of the project through oral presentation, written and visual formats, demonstrating academic and professional standards.

Data science project, under supervisory guidance, will involves formulating a clear research question aligned with advanced academic or industry objectives, identifying and acquiring high-quality datasets, and performing rigorous data pre-processing and exploratory analysis. It will also require selecting and justifying appropriate statistical or machine learning techniques, implementing models with reproducibility and ethical considerations, while critically evaluating results against theoretical frameworks or benchmarks.
Once the project proposal has been submitted and approved at the designated stage, the student will proceed with independent research, culminating in a comprehensive dissertation. This dissertation will demonstrate academic rigor through a clearly defined problem statement, an in-depth literature review, a detailed and justified methodology, reproducible code, validated models, insightful visualizations, and a critical discussion of findings, all supported by properly referenced sources.
Taught part contents:
High-level conceptual themes that students should engage with before starting their Level 7 project include the following:
Principles of Responsible Data Management, Strategic Project Planning and Control, Stakeholder Analysis and Engagement, Professional Communication and Dissemination, Research Governance and Quality Assurance, Critical Thinking and Decision-Making.

Viva: 25% weighting, 50% pass mark.
Learning Outcomes: 1 - 5
Duration: 14 minutes
Outline Details: A presentation/viva in which the student presents their research

Project: 75% weighting, 50% pass mark.
Learning Outcomes: 1 - 5
Word Length: 6000.
Outline Details: Management, implementation and evaluation of a Data Science project.