Topics in Scientific Computing

Full course description

MAT2004 Linear Algebra

MAT2006 Calculus

MAT2007 Introduction to Programming

Recommended

KEN1540 Numerical Methods

Special Requirements

For this course you will need to use your own laptop (no tablet/I-pad) The practical will use Matlab

Objectives

Students are expected to:

Understand the role of computers to analyse and solve problems in various scientific domains.

Learn several algorithms for scientific computing, the problems they solve, and why they are important.

Gain experience implementing algorithms and applying them to scientific problems.

Description of the skill

Scientific computing concerns the use of computers to analyse and solve problems arising in a wide range of disciplines including biology, chemistry, and physics. In this course, students will gain and understanding for and develop solutions to a selection of these problems. Specifically, they will examine frequency domain analysis for signal processing; machine learning for cluster analysis; principal component analysis for dimensionality reduction; linear regression for regression analysis; finite-difference solvers for partial differential equations; and combinatorial optimisation for phylogenetic reconstruction. This course is complemented by KEN1540 Numerical Methods, a course in which students learn the basic algorithms of scientific computing in more depth. Python will be the language of instruction for this course.