COM7022 Assignment Brief
As part of the formal assessment for the programme you are required to submit a Machine Learningassignment. Please refer to your Student Handbook for full details of the programme assessment scheme and general information on preparing and submitting assignments. The assignment brief will specifically give details and instructions for the assignment. No examination, or details of, are included within this module.
Module description: Coursework 100%
Description: The assignment is given as two tasks. Each task is to be answered individually, unless multiple components have been given. Task 1 has been designed to check your understanding of Machine Learning methodologies for critical analysis, through a real-world mini Machine Learning project. All of which will be written in Python
Task 2 is designed to give you the opportunity to demonstrate your Machine Learning reporting skills, comprehensively written in an easily understandable manner, based upon your investigation.
Learning Outcomes:
| Criteria / Learning Outcome | Coursework |
|---|---|
| Demonstrate a practical understanding of the characteristics of various Machine Learning methods and their applications in data analysis (LO 1) | X |
| Select and apply appropriate machine learning techniques for a given scenario (LO 2) | X |
| Critically evaluate the results from the application of Machine Learning techniques and propose improvements (LO 3) | X |
| Graduate Attribute: Critically evaluate and further contextualise understanding of the subject area with the ability to link the discipline(s) to local, national and global issues, research and pursue evidence-based arguments within the discipline using an extensive range of academic and professional body resources. Show clear ability to engage with different traditions of thought and apply knowledge in practice, including in multi-disciplinary or multi-professional contexts (LO 4) |
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