Data Mining (Level 8)

1. Display a comprehensive understanding of different data mining tasks and the algorithms most appropriate for addressing them.
2. Evaluate models/algorithms with respect to their accuracy.
3. Demonstrate capacity to perform a self-directed piece of practical work that requires the application of data mining techniques.
4. Critique the results of a data mining exercise.
5. Develop hypotheses based on the analysis of the results obtained and test them.
6. Conceptualise a data mining solution to a practical problem.

The Data Mining module is assessed by 20% continuous assessment and 80% proctored examination. The grades will accumulate over the two semesters. The use of continuous assessment is based on developing the learner’s ability to investigate, evaluate theories and concepts and apply them to a given scenario.

The 80% Proctored Written Examination will be case study based. The case study will be issued two hours before the examination for review. The examination will be two hours in duration and all questions will be based on the case study. Learners will be required to demonstrate the learning of concepts, theories etc by identifying issues in the case study and offering recommendations, with justifications.

Questions in the examination will be linked requiring learners to complete/attempt the first question before attempting the second and so on.

Mapping of Assessments to Module Learning Outcomes

Where the combined marks of the assessment and examination do not reach the pass mark the learner will be required to repeat the element of assessment that they failed. Reassessment materials will be published on Moodle after the Examination Board Meeting and will be aligned to the MIMLOs and learners will be capped at 40% unless there are personal mitigating circumstances.