AMS2002 - Optimisation for Data Science
|Year of Study:||2 - 4|
|Prerequisites:||AMS1001 Introduction to Linear Algebra and Calculus or with the Instructor’s permission and upon endorsement of the relevant Head or Programme Director. Exclusion: AMS2001 Quantitative Methods for Business Management|
This module aims to provide students with the optimisation techniques which are widely adopted in data science. Students will be able to acquire techniques to tackle linear programming problems as well as unconstrained and constrained optimisation problems. Real life applications are provided to illustrate the methodologies.
Upon completion of this module, students should be able to:
- examine the significance and understand the basic concepts and theories of optimization;
- apply linear programming methodologies;
- apply unconstrained optimization techniques; and
- apply constrained optimization techniques.