MATH2601 is a Mathematics Level II course; it is the higher version of MATH2501 Linear Algebra. See the course overview below.

Units of credit: 6

Prerequisites: MATH1231 or MATH1241 or MATH1251, each with a mark of 70 or higher.

Exclusions: MATH2501

Cycle of offering: yearly in Semester 2.

Graduate attributes: the course will enhance your research, inquiry and analytical thinking abilities.

More information: this recent course handout (pdf) contains information about course objectives, assessment, course materials and the syllabus. (This pdf will usually be updated by the end of the first week of the semester.)

The Online Handbook entry contains up-to-date timetabling information.

MATH2601 (alternatively MATH2501) is a compulsory course for Mathematics and Statistics majors.

If you are currently enrolled in MATH2601, you can log into the My eLearning Vista instance of this course.

The principal aim of this course is to encourage students to develop a working knowledge of the central ideas of linear algebra: vector spaces, linear transformations, orthogonality, eigenvalues, eigenvectors and canonical forms and the applications of these ideas in science and engineering.

A secondary objective is to understand how certain calculations in linear algebra can be thought of as algorithms, that is as a fixed method which will lead in finite time to solutions of whole classes of problems.
Applications of linear algebra to geometry and ordinary differential equations will be included, as well as some general applications used in
engineering.

A third objective is to introduce students to one of the major themes of modern mathematics: classification of structures and objects, such as the group, the field and the vector space. Using linear algebra as a model, we will look at techniques that allow us to can tell when two apparently different objects can be treated as if they were the same(isomorphic). We will include a brief introduction to group theory, concentrating on groups of matrices.

Modern application of Linear Algebra rely very heavily on the computer, and in some cases are driven by computer oriented applications. We will therefore make use of MAPLE. For some work in the course matlab may also be suitable.