Assessment Overview¶
Submission Requirements¶
| Component | Weight | Format |
|---|---|---|
| Oral Presentation | 75% | Max 20 minutes — MP4 video, voice-over PPTX, or SharePoint recording |
| Slide Deck | 25% | Max 12 slides — PPTX or PDF + reference appendix |
Presentation Structure¶
Your presentation must include:
- Executive Summary — one-slide overview of your ML solution and key findings
- Background — business context, problem statement, hypothesis
- Section A: Methodology — data preparation, feature engineering, model selection, justify all choices
- Section B: Results — model performance metrics, validation approach, comparison of models
- Section C: Impact & Conclusion — business impact, recommendations, limitations, future work
Marking Criteria¶
| Criterion | Weight | What Examiners Look For |
|---|---|---|
| Knowledge & Understanding | 15% | Correct application of ML techniques |
| Critical Analysis | 15% | Thoughtful interpretation of results |
| Scientific Approach | 15% | Hypothesis-driven methodology |
| Communication | 15% | Clear, structured presentation of conclusions |
| Business Impact | 15% | Link ML outcomes to organisational goals |
| Slide Presentation | 15% | Professional, engaging, well-structured slides |
| Academic Skills | 5% | Reflective, structured approach |
| Referencing | 5% | Harvard style, academic + industry sources |
Suitable ML Techniques¶
The brief lists these as appropriate:
- Linear Regression / Logistic Regression
- Time Series (ARIMA, SARIMA)
- Ensemble models (Random Forest, Gradient Boosting)
- Clustering algorithms
- Other (e.g., deep learning — with justification)
GenAI Usage Rules¶
Read This Carefully
Permitted: Brainstorming structure, feedback on drafts, coding syntax help, research assistance.
Prohibited: Generating presentation script verbatim, creating ML outputs/visualisations, performing analysis, writing slide content, synthetic voice.
You must declare all GenAI usage and include prompts/outputs in your appendix.