Enquiry for Science Major/Minor/Programme Requirements
MATH2101 Linear algebra I (6 credits) Academic Year 2025
Offering Department Mathematics Quota ---
Course Co-ordinator Dr K Y Chan, Mathematics < kychan@maths.hku.hk >
Teachers Involved (Dr K Y Chan,Mathematics)
(Dr V Bhat,Mathematics)
Course Objectives This is a first university level course on linear algebra, which aims at introducing to students the basic concept of linear structure through many concrete examples in the Euclidean spaces. The course also enriches students' exposure to mathematical rigor and prepares them for studying more advanced mathematical courses.
Course Contents & Topics - Matrix Algebra: Matrix addition and multiplication, determinant and inverse of square matrices, system of linear equations as a matrix equation.
- Systems of Linear Equations: Gauss-Jordan elimination, elementary row operations, row echelon form, elementary matrices, matrix inversion.
- Vector Spaces: Coordinate system in R^n, the Euclidean spaces as vector spaces, its subspaces, span of vectors, linear independence, basis, dimension, applications.
- Linear transformations: Definition and examples of linear transformations between Euclidean spaces, matrix representations, and change of coordinates.
- Eigenvalue Problem: Eigenvalues and eigenvectors, diagonalization of matrices, applications.
- Inner Product: Gram-Schmidt process, least square problems and orthogonal matrices.
Course Learning Outcomes
On successful completion of this course, students should be able to:

CLO 1 handle matrix operations and use them in some practical problems
CLO 2 solve systems of linear equations by Gauss-Jordan elimination and also compute inverses of square matrices
CLO 3 understand the concept of vector spaces, basis, dimension, and linear transformations and compute the matrix representations of some linear transformations
CLO 4 solve some simple eigenvalue problems and apply the theory to some practical problems
CLO 5 solve some practical problems involving the least square concept
Pre-requisites
(and Co-requisites and
Impermissible combinations)		 Pass in MATH1013 or MATH1821 or MATH1853
Course Status with Related Major/Minor /Professional Core 2025 Major in Mathematics ( Core/Compulsory )
2025 Major in Mathematics (Intensive) ( Core/Compulsory )
2025 Minor in Computational & Financial Mathematics ( Disciplinary Elective )
2025 Minor in Mathematics ( Disciplinary Elective )
2025 Minor in Operations Research & Mathematical Programming ( Disciplinary Elective )
2024 Major in Mathematics ( Core/Compulsory )
2024 Major in Mathematics (Intensive) ( Core/Compulsory )
2024 Minor in Computational & Financial Mathematics ( Disciplinary Elective )
2024 Minor in Mathematics ( Disciplinary Elective )
2024 Minor in Operations Research & Mathematical Programming ( Disciplinary Elective )
2023 Major in Mathematics ( Core/Compulsory )
2023 Major in Mathematics (Intensive) ( Core/Compulsory )
2023 Minor in Computational & Financial Mathematics ( Disciplinary Elective )
2023 Minor in Mathematics ( Disciplinary Elective )
2023 Minor in Operations Research & Mathematical Programming ( Disciplinary Elective )
2022 Major in Mathematics ( Core/Compulsory )
2022 Major in Mathematics (Intensive) ( Core/Compulsory )
2022 Minor in Computational & Financial Mathematics ( Disciplinary Elective )
2022 Minor in Mathematics ( Disciplinary Elective )
2022 Minor in Operations Research & Mathematical Programming ( Disciplinary Elective )
2021 Major in Mathematics ( Core/Compulsory )
2021 Major in Mathematics (Intensive) ( Core/Compulsory )
2021 Minor in Computational & Financial Mathematics ( Disciplinary Elective )
2021 Minor in Mathematics ( Disciplinary Elective )
2021 Minor in Operations Research & Mathematical Programming ( Disciplinary Elective )
Course to PLO Mapping 2025 Major in Mathematics < PLO 1,2,3 >
2025 Major in Mathematics (Intensive) < PLO 1,2,3 >
2024 Major in Mathematics < PLO 1,2,3 >
2024 Major in Mathematics (Intensive) < PLO 1,2,3 >
2023 Major in Mathematics < PLO 1,2,3 >
2023 Major in Mathematics (Intensive) < PLO 1,2,3 >
2022 Major in Mathematics < PLO 1,2,3 >
2022 Major in Mathematics (Intensive) < PLO 1,2,3 >
2021 Major in Mathematics < PLO 1,2,3 >
2021 Major in Mathematics (Intensive) < PLO 1,2,3 >
Offer in 2025 - 2026 Y        1st sem    2nd sem    Examination Dec    May     
Offer in 2026 - 2027 Y
Course Grade A+ to F
Grade Descriptors
A Demonstrate an excellent understanding of key concepts and ideas by being able to identify the appropriate theorems and their applications through correctly analysing problems, clearly and elegantly presenting correct logical reasoning and argumentation and being able to carry out computations carefully and correctly, and with some innovative approaches to solving problems.
B Demonstrate a good understanding of key concepts and ideas by being able to identify the appropriate theorems and their applications through correctly analysing problems, but with some minor inadequacies in arguments, identifying the appropriate theorems or their applications and presentation or with some minor computational errors.
C Demonstrate an acceptable understanding of key concepts and ideas by being able to correctly identify appropriate theorems, but with some inadequacies in applying the theorems through incorrectly analysing problems with poor argument and presentation or a number of minor computational errors.
D Demonstrate some understanding of key concepts and ideas by being able to correctly identify appropriate theorems, but with substantial inadequacies in applying the theorems through incorrectly analysing problems with poor argument or presentation or with substantial computational errors.
Fail Demonstrate poor and inadequate understanding by not being able to identify appropriate theorems or their applications, or not being able to complete the solution.
Communication-intensive Course N
Course Type Lecture-based course
Course Teaching
& Learning Activities
Activities Details No. of Hours
Lectures 36.0
Tutorials 12.0
Reading / Self study 100.0
Assessment Methods
and Weighting
Methods Details Weighting in final
course grade (%)		 Assessment Methods
to CLO Mapping
Assignments 20.0 1,2,3,4,5
Examination 50.0 1,2,3,4,5
Test 30.0 1,2,3,4,5
Required/recommended reading
and online materials		 Spence, Insel & Friedberg: Elementary Linear Algebra -- A Matrix Approach (Pearson, 2014)
Course Website http://moodle.hku.hk/
Additional Course Information


Back  /  Home