Numerical Optimisation
offered by Oxford University

Public University
1 Campus
Estd. 1096

Numerical Optimisation
at
Oxford University
Overview

Learn everything you need to know about integer programming & genetic programming and give a boost to your professional career

Duration	10 weeks
Total fee	₹25,500
Mode of learning	Online
Course Level	UG Certificate

Numerical Optimisation
at
Oxford University
Highlights

Earn a certificate of completion from Oxford university

Numerical Optimisation
at
Oxford University
Course details

What are the course deliverables?

State-of-the-art
Techniques for solving optimisation problems
Continuous and discrete
Linear and non-linear
Constrained and unconstrained

More about this course

This course is intended to provide a thorough background of computational methods for the solution of constrained and unconstrained optimisation problems, and linear and nonlinear programming tasks
Particular attention will be given to the description and analysis of methods that can be used to solve practical problems
Although the focus is on methods, the theoretical underpinnings of the problems and the mathematical properties of the algorithms designed to solve them are systematically developed
To introduce and develop mathematical techniques for solving linear and non-linear and constrained and unconstrained optimisation problems, using state-of-the art techniques

Numerical Optimisation
at
Oxford University
Curriculum

Week 1

Structure of methods: Line search techniques

Week 2

Newton methods and methods of steepest descent

Week 3

Conjugate Gradient Methods: the linear conjugate gradient method

Week 4

Conjugate Gradient Methods: the non-linear conjugate gradient method

Week 5

Stochastic Gradient Descent

Week 6

Linear programming and game theory

Week 7

Integer programming

Week 8

Genetic programming

Week 9

Algorithms for non-linear constraint optimisation: fundamentals

Week 10

Algorithms for non-linear constraint optimisation: Quadratic programming

Numerical Optimisation
at
Oxford University
Faculty details

Dr Mcebisi Ntleki

Dr Ntleki obtained his DPhil in Oxford on a topic in computational biolinguistics. He has taught courses in mathematics, statistics and statistical programming using medium size and large data sets arising in medical research: sequential MCMC, using R, and Deep learning and computer vision using Python.

Numerical Optimisation
at
Oxford University
Entry Requirements

Eligibility criteria Up Arrow Icon

Prerequisite: Basic knowledge of Linear algebra, Multivariate real analysis, Multivariable calculus

Conditional Offer Up Arrow Icon

Yes
In countries where the normal examinations have been cancelled, university will expect the conditions of student's offer to be met by the alternative assessment put in place by qualifications' regulators.