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Curricular information is subject to change
Upon successful achievement of the learning outcomes the student will be able to:
Prove elementary facts and identities related to the axioms of a vector space.
State and unpack the fundamental definitions of linear algebra.
State and prove the key theorems in the subject.
Determine whether or not given sets of vectors form a vector subspace.
Compute the span of a set of vectors.
Decide if a set of vectors are linearly independent or not.
Calculate the basis and dimension of a vector space.
Apply the Rank-Nullity theorem.
Find the image and nullspace of a linear transformation along with their bases.
Calculate the change of basis matrix.
Calculate the characteristic polynomial, eigenvalues, eigenvectors, and eigenspaces of a linear transformation.
Determine when a linear transformation is diagonalzable and when it is not.
Prove facts about inner product spaces.
Apply known results to unseen problems and applications.
Student Effort Type | Hours |
---|---|
Lectures | 23 |
Tutorial | 12 |
Autonomous Student Learning | 51 |
Online Learning | 24 |
Total | 110 |
A good first year knowledge of undergraduate linear algebra will be assumed, such as that given in MATH10340, or its equivalent from other universities.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Examination: Final examination held at the end of the trimester | 2 hour End of Trimester Exam | No | Graded | No | 50 |
Examination: Mid-trimester exam to be held halfway through the course. No remediation. |
Week 7 | No | Graded | No | 30 |
Continuous Assessment: 5 Homework assignments spread across the term. No remediation. | Varies over the Trimester | n/a | Graded | No | 20 |
Resit In | Terminal Exam |
---|---|
Spring | Yes - 2 Hour |
• Feedback individually to students, on an activity or draft prior to summative assessment
• Group/class feedback, post-assessment
• Peer review activities
• Self-assessment activities
An important part of this module is self-directed learning and knowing when a submission is good enough to meet the module's learning outcomes. Therefore you will have opportunities to review your peers' work as well as having your own work reviewed by your peers BEFORE submission.
Name | Role |
---|---|
Andrew Mullins | Tutor |
Lecture | Offering 1 | Week(s) - Autumn: All Weeks | Mon 09:00 - 09:50 |
Lecture | Offering 1 | Week(s) - Autumn: All Weeks | Wed 09:00 - 09:50 |
Tutorial | Offering 1 | Week(s) - Autumn: All Weeks | Thurs 09:00 - 09:50 |
Tutorial | Offering 3 | Week(s) - Autumn: All Weeks | Tues 10:00 - 10:50 |