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Curricular information is subject to change
- Why Data Mining and what is Data Mining?
- What is Data Warehouse and its architecture?
- Understand multi-dimensional data model.
- Understand the data pre-processing phase.
- Understand core functions of Data Mining.
- Classification, clustering and association rules .
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Student Effort Type | Hours |
---|---|
Lectures | 24 |
Practical | 24 |
Autonomous Student Learning | 76 |
Total | 124 |
Not applicable to this module.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Multiple Choice Questionnaire: short examination during the semester | Varies over the Trimester | n/a | Graded | No | 40 |
Lab Report: These are submissions of tutorial or practical work that have been carried out in 2-hour tutorial/practical sessions. | Varies over the Trimester | n/a | Graded | No | 20 |
Examination: End of semester exam | 2 hour End of Trimester Exam | No | Graded | No | 40 |
Resit In | Terminal Exam |
---|---|
Spring | Yes - 2 Hour |
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Online automated feedback
The students will be given feedback on their tutorial or practical work within 2 weeks following their submissions.
Lecture | Offering 1 | Week(s) - Autumn: All Weeks | Thurs 11:00 - 11:50 |
Lecture | Offering 1 | Week(s) - Autumn: All Weeks | Tues 13:00 - 13:50 |
Practical | Offering 1 | Week(s) - Autumn: All Weeks | Tues 16:00 - 17:50 |
Practical | Offering 2 | Week(s) - 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12 | Wed 13:00 - 14:50 |
Practical | Offering 2 | Week(s) - 5 | Wed 13:00 - 14:50 |