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  • Leicester rated in top 10 cities to start a sustainable tech business

    Leicester has been rated in the top 10 cities in the UK to start a sustainable tech business. The list, compiled by Business Zone, highlights Leicester among the cities leading the way by setting the right foundations for success.

  • Citizens of Change

    Discover the benefits of studying here at Leicester by ordering either an undergraduate or postgraduate prospectus.

  • Risk reduction

    How can I reduce my risk of developing a wound infection identifies options of how to stay healthy prior to surgery

  • Research

    Members of the Centre have undertaken research on topics as diverse as the nineteenth-century afterlives of Romantic poets, the discourse of the sublime in poetry, art and criticism, and Victorian theatre - to name but a few.

  • Andrew Hyam BSc MA

    Learn more about our Senior Supervisor of ULAS, Andrew Hyam.

  • The Business Environment

    Module code: MK1001 This module explores the issue of how external forces shape organisational strategy and business performance in national and international contexts.

  • Writing for Laughs

    Module code: EN3204 This module aims to mix creative writing, criticism and theory in its exploration of modern and contemporary comedy.

  • Advanced Statistical Modelling (Part-time)

    Module code: MD7468 Generalised linear models This module will start by introducing the theory of generalized linear models (GLMs) in terms of exponential family of distributions and discussing special cases of GLMs, such as normal, Poisson or binomial regression.

  • Business Taxation

    Module code: AF2085/AF3085 This module provides an introduction to the key UK business taxes, and is one of two accredited modules which together give exemption from the basic taxation exams for the ICAEW, ICAS and ACCA professional bodies.

  • Advanced Statistical Modelling (Part-time)

    Module code: MD7468 Generalised linear models This module will start by introducing the theory of generalized linear models (GLMs) in terms of exponential family of distributions and discussing special cases of GLMs, such as normal, Poisson or binomial regression.

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