Matrices and Complex Numbers
Undergraduate: Level 5
Thursday 03 October 2019
Saturday 14 December 2019
01 October 2019
Requisites for this module
EC114, MA201, MA204, MA205, MA225, MA301, MA306, MA314, MA317
BSC I1G3 Data Science and Analytics,
BSC I1GB Data Science and Analytics (Including Placement Year),
BSC I1GC Data Science and Analytics (Including Year Abroad),
BSC I1GF Data Science and Analytics (Including Foundation Year)
This module introduces students to the basics of linear algebra, emphasising vectors and matrices.
The aim of this module is to provide BSc Data Science and Analytics students with basics of linear algebra, emphasising vectors and matrices.
On completion of the module students should be able to: understand the geometric and algebraic properties of vectors in two- and three-dimensional
Euclidean space; perform simple operations on matrices; solve systems of linear equations using row operations; calculate the determinant and the inverse of a matrix; calculate the eigenvalues and eigenvectors of a matrix; diagonalize a symmetric matrix; understand linear mappings, projection matrices, singular value decomposition of quadratic forms; apply linear mappings, projection matrices, singular value decomposition of quadratic forms using data science software such as R or Python.
- Addition, subtraction, multiplication and division of complex numbers in both Cartesian and polar form;
- de Moivre's theorem;
- complex nth roots.
- Geometry and algebra of R2 and R3;
- vector addition and scalar multiplication.
- matrix addition and multiplication, scalar multiplication;
- systems of linear equations;
- Gaussian elimination, elementary row operations;
- identity and inverse matrices, determinants;
- eigenvalues and eigenvectors;
- diagonalization of symmetric matrices;
- applications to quadratic forms in two and three dimensions;
- matrices of linear mappings;
- projection matrices;
- singular value decomposition of quadratic forms.
This module consists of 20 lectures, 10 classes and five labs. There are three revision lectures in the Summer term.
This module does not appear to have a published bibliography.
Assessment items, weightings and deadlines
|Coursework / exam
||120 minutes during Summer (Main Period) (Main)
Module supervisor and teaching staff
Dr Alexei Vernitski, email firstname.lastname@example.org
Dr Alexei Vernitski (email@example.com)
No external examiner information available for this module.
Available via Moodle
Of 64 hours, 13 (20.3%) hours available to students:
51 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
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