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Curricular information is subject to change
Ability to encode large amounts of information using matrices and then efficiently extracting important parts using linear algebra. Understanding stochastic matrices and how to apply their properties in ranking data.
Indicative Module Content:Student Effort Type | Hours |
---|---|
Lectures | 24 |
Autonomous Student Learning | 70 |
Online Learning | 12 |
Total | 106 |
A knowledge of basic linear algebra (covered in first level linear algebra modules) is needed.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Examination: Final examination | 2 hour End of Trimester Exam | No | Standard conversion grade scale 40% | No | 70 |
Continuous Assessment: Varies over the semester | Unspecified | n/a | Standard conversion grade scale 40% | No | 30 |
Resit In | Terminal Exam |
---|---|
Autumn | Yes - 2 Hour |
• Group/class feedback, post-assessment
Not yet recorded.
Name | Role |
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Ms Ciara Murphy | Tutor |