Undergraduate Course: Linear Algebra 1 (MATH08079)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 8 (Year 1 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This is a course in concrete, computational linear algebra. The aim is to provide students with a nuts-and-bolts mastery of the basic computations and manipulations in linear algebra, as well as an appreciation of its wide-ranging applications. This knowledge is a crucial requirement for later courses in pure and applied mathematics, as well as operational research and statistics.
A representative outline of the course is: Vectors, Dot product, Matrices, Systems of linear equations, Gaussian elimination, Matrix algebra, Determinants, Kernel, image, Rank-nullity theorem, Eigenvalues, Singular value decomposition. |
| Course description |
This is a first course in linear algebra, with a focus on concrete, computational approaches and applications. It will introduce students to vectors and matrices in R^n, and allow them to develop
conceptual understanding and mastery of a range of ideas and techniques, such as the dot product, solving systems of linear equations, matrix algebra, determinants, and decomposition of matrices. The course will also cover a wide range of applications, both to motivate the concepts introduced, and to allow students to practise their linear algebra skills.
Linear algebra is one of the key areas of mathematics which underpins a large part of students' future studies, both through more theoretical generalizations in abstract algebra, and in more concrete domains such as applied mathematics, statistics, operational research, and data science.
Summary of student experience: You will be introduced to fundamental concepts and techniques in linear algebra through the study of vectors and matrices. This will include mastering a range of computational techniques and developing an appreciation for the wide variety of mathematical areas in which they have applications. You will also develop your critical thinking skills through verification of calculations. This knowledge and skill set will be the foundation for many areas of further mathematical study.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
Introduction to Mathematics at University (MATH08078)
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | Due to limitations on class sizes, students will only be enrolled on this course if it is specifically referenced in their DPT. Students on programmes for which this course is compulsory are not required to take the prerequisite course. |
Information for Visiting Students
| Pre-requisites | This is a Year 1 course. Visiting students should have passed courses equivalent to Introduction to Mathematics at University (MATH08078). |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2025/26, Available to all students (SV1)
|
Quota: 0 |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 33,
Dissertation/Project Supervision Hours 16.5,
Summative Assessment Hours 3,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
143 )
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| Assessment (Further Info) |
Written Exam
80 %,
Coursework
20 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Coursework: 20%
Examination: 80%
Students must pass exam and course overall. |
| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Minutes |
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| Main Exam Diet S2 (April/May) | MATH08079 Linear Algebra 1 | 180 | |
Learning Outcomes
On completion of this course, the student will be able to:
- For a given matrix, compute its kernel, image, and (when meaningful) its determinant, and inverse.
- Demonstrate mastery of fundamental computations in vector and matrix algebra, as well as an understanding of applications of these approaches.
- Demonstrate understanding of the rank-nullity theorem and how it is used.
- Perform standard computations in linear algebra both by hand and using appropriate software.
- Confirm the correctness, or otherwise, of computations with simple verifications.
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Reading List
Nicolson, Linear Algebra with Applications
Strang, Introduction to Linear Algebra
Feeman, Applied Linear Algebra and Matrix Methods |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Linear Algebra,Vectors,Matrices,Systems of Linear Equations,LA1 |
Contacts
| Course organiser | Dr Ana Rita Pires
Tel: (0131 6)50 5079
Email: apires@ed.ac.uk |
Course secretary | Ms Louise Durie
Tel: (0131 6)50 5050
Email: L.Durie@ed.ac.uk |
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