Postgraduate Diploma Optimisation and Data Analytics
Our Postgraduate Diploma Optimisation and Data Analytics is aimed at those with a first degree in which the major subject was mathematics, and we expect you to have prior knowledge of statistics – for example significance testing or basic statistical distributions – and operational research such as linear programming.
Postgraduate Diplomas last for six to nine months (full-time) and include the modules and assessed work of a Masters, without a dissertation. This allows you to proceed to a Masters in mathematics if your undergraduate degree was in a different subject.
Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Working in this field, you might be identifying future needs for a business, evaluating the time-life value of a customer, or carrying out computer simulations for airlines.
You specialise in areas including:
- Continuous and discrete optimisation
- Time series econometrics
- Heuristic computation
- Experimental design
- Machine learning
- Linear models
Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines.
Our Department of Mathematical Sciences has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.
We are genuinely innovative and student-focused. Our research groups are working on a broad range of collaborative areas tackling real-world issues. Here are a few examples:
- Our data scientists carefully consider how not to lie, and how not to get lied to with data. Interpreting data correctly is especially important because much of our data science research is applied directly or indirectly to social policies, including health, care and education.
- We do practical research with financial data (for example, assessing the risk of collapse of the UK’s banking system) as well as theoretical research in financial instruments such as insurance policies or asset portfolios.
- We also research how physical processes develop in time and space. Applications of this range from modelling epilepsy to modelling electronic cables.
- Our optimisation experts work out how to do the same job with less resource, or how to do more with the same resource.
- Our pure maths group are currently working on two new funded projects entitled ‘Machine learning for recognising tangled 3D objects’ and ‘Searching for gems in the landscape of cyclically presented groups’.
- We also do research into mathematical education and use exciting technologies such as electroencephalography or eye tracking to measure exactly what a learner is feeling. Our research aims to encourage the implementation of ‘the four Cs’ of modern education, which are critical thinking, communication, collaboration, and creativity.
Our Postgraduate Diploma Optimisation and Data Analytics is aimed at those with a first degree in which the major subject was mathematics, and we expect you to have prior knowledge of statistics – for example significance testing or basic statistical distributions – and operational research such as linear programming.
Postgraduate Diplomas last for six to nine months (full-time) and include the modules and assessed work of a Masters, without a dissertation. This allows you to proceed to a Masters in mathematics if your undergraduate degree was in a different subject.
Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Working in this field, you might be identifying future needs for a business, evaluating the time-life value of a customer, or carrying out computer simulations for airlines.
You specialise in areas including:
- Continuous and discrete optimisation
- Time series econometrics
- Heuristic computation
- Experimental design
- Machine learning
- Linear models
Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines.
Our Department of Mathematical Sciences has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.
We are genuinely innovative and student-focused. Our research groups are working on a broad range of collaborative areas tackling real-world issues. Here are a few examples:
- Our data scientists carefully consider how not to lie, and how not to get lied to with data. Interpreting data correctly is especially important because much of our data science research is applied directly or indirectly to social policies, including health, care and education.
- We do practical research with financial data (for example, assessing the risk of collapse of the UK’s banking system) as well as theoretical research in financial instruments such as insurance policies or asset portfolios.
- We also research how physical processes develop in time and space. Applications of this range from modelling epilepsy to modelling electronic cables.
- Our optimisation experts work out how to do the same job with less resource, or how to do more with the same resource.
- Our pure maths group are currently working on two new funded projects entitled ‘Machine learning for recognising tangled 3D objects’ and ‘Searching for gems in the landscape of cyclically presented groups’.
- We also do research into mathematical education and use exciting technologies such as electroencephalography or eye tracking to measure exactly what a learner is feeling. Our research aims to encourage the implementation of ‘the four Cs’ of modern education, which are critical thinking, communication, collaboration, and creativity.
