This module provides you with a foundation in mathematics and statistics which will allow you a smooth transition to an undergraduate module containing quantitative material.
This module offers an introduction to the differential and integral calculus that underpins engineering mathematics.
This module provides students with some fundamental mathematical concepts relevant to applications in AI and CE. The focus will be on applying mathematical proofs to solve computer science problems as well as introducing basic concepts and techniques in linear algebra and calculus. In addition to theoretical treatments, there will be laboratory applications using Python and Jupyter to visualize, manipulate and explore mathematics.
This module provides students with fundamental mathematical concepts relevant to applications in AI and CE. The focus will be on probability, statistical inference, combinatorics, optimization techniques, calculus – partial derivatives and ordinary differential equations, and symbolic maths. There will be laboratory applications using Python and Jupyter to visualise, manipulate and explore these topics.
This module provides a bridge between A-level mathematics and university mathematics. It provides a good grounding and an in depth understanding of the theory and application of differential calculus, and other techniques widely used in Economics and Finance. It is aimed at students who hold an A level in Mathematics at Grade B or above. Topics of study include functions, univariate optimisation, elasticity, financial mathematics, multivariate optimisation, constrained optimization, matrices, integration, difference and differential equations, and Taylor/Maclaurin series expansions. The module is designed to prepare students for more advanced quantitative modules in 2nd and 3rd year. It also complements the teaching of first year microeconomics and macroeconomics modules.
This course lays the mathematical foundation for all engineering degrees. Its structure allows students with different levels of previous knowledge to work at their own pace. Pre-requisite for MATH2048 One of the pre-requisites for MATH3081 and MATH3082
The module aims to teach mathematical methods relevant for engineering. The first part is about differential equations and how solve them, from ordinary differential equations to partial differential equations. The second part is about either vector calculus (for Mech, Ship, Aero and ISVR) or statistics (for Civil Engineering). There are 3 lectures and 1 problem class per week. Problems are assigned each week. They are discussed in the problem class and then the solutions are posted on blackboard. Feedback and student support during module study (formative assessment) - Entire cohort: 4 on-line coursework assignments, which are marked as soon as they are completed and the corrected answers are given. Fully worked out solutions are posted on blackboard after the deadline. For Mech, Ship, Aero and ISVR: 2 additional on-line coursework. For Civil Engineering: coursework in the form of Minitab exercises - 1 class test - Lecture notes, coursework assignments, solutions and past examination papers available on the blackboard site One of the pre-requisites for MATH3083 and MATH3084
This module is designed to provide students with the mathematics knowledge and skills required for a successful transition to degree-level study in disciplines related to the chemical and biological sciences. The material covered is at a level corresponding to pre-university qualifications such as AS level in the UK.
This module aims to: - Introduce the logical and mathematical foundations of computer science. - Illustrate the use of formal languages in computer science, including in algorithms and programming. - Extend students' mathematical sophistication and skills. - Present basic concepts and techniques of combinatorics, statistics and probability. - Give mathematical background necessary for other compulsory modules. - Develop the study skills necessary for students to learn new concepts of mathematics and programming (including those we do not cover in the degree). - Instill a range of useful problem solving skills.
This module aims to cover the continuous mathematics that's required for the computer science and software engineering programmes.
Machine Learning is about extracting useful information from large and complex datasets. Although driven by applications, the techniques used are based on a broad mathematical basis. This course provides the mathematical foundations of the subject from functional analysis through to optimisation, convexity and information theory.
This module is compulsory for every Year 3 student of any Mathematical Sciences degree programme. Its main goal is to provide the student with an opportunity to research an area of mathematics that interests them, while strengthening their transferrable skills and supporting them in growing their CV and achievements that will make them more attractive to employers. As to the latter, there will be specific sessions devoted to various topics related to employability, CV preparation, and other aspects of job hunting. The remainder of this module overview is however about the former, the main part of this module. This module provides an opportunity to develop skills and knowledge in an area of mathematical science that excites the student and matches their particular strengths. We will provide support to guide the student through their research and report preparation, while giving them the freedom to explore the subject on their own. Support is provided through plenary lectures and through individual (roughly bi-weekly) supervision meetings. The work may involve directed reading of books or original papers in journals and the provision of examples to illustrate particular aspects of a topic. Some topics may also present the opportunity for students to pursue their own investigations, undertake practical work using the computer or working on a project brief from an industry partner. In summary, the student will learn how to: (a) Write up a report on their topic: a preliminary report at the end of Semester 1 leading to feedback and advice followed by a completed final report at the end of Semester 2. (b) Carry out a literature survey appropriate to their topic and how to use a wide variety of sources in an imaginative way, how to give proper credit to the work of others, and in particular what constitutes and how to avoid plagiarism. (c) Present their work to a small audience. This is great training for communicating a technical subject succinctly, and a skill a student will definitely use after graduating. There is an opportunity to present their work both at the end of Semester 1 and at the end of Semester 2.
‘I have here in my hand a list of 205 names that were made known to the Secretary of State as being members of Communist Party and who nevertheless are still working and shaping policy in that State Department.' With these words, asserting both the existence of an internal communist menace and the government failure to act against it, Senator Joseph McCarthy thrust himself into the centre of US national politics. His inquisition into communist subversives and spies lasted from 1950 to 1954. But ‘McCarthyism' as a phenomenon was more deeply-rooted, more enduring and much broader in scope than the career and campaigns of a single politician. This module explores the causes, course and effects of McCarthyism writ large, from the end of the Second World War through to the late 1950s.
In the contemporary business environment, marketing accountability is constantly increasing in importance. Being able to measure marketing performance and demonstrate how effectively marketing is conducted in organisations has also become a source of performance differentials between companies. This module introduces and discusses key marketing metrics for evaluating marketing effectiveness, providing insights into marketing performance measurement in organisations.
In the contemporary business environment, data-based marketing is constantly increasing in importance. Being able to measure marketing performance and demonstrate how effectively marketing is conducted in organisations has also become a source of performance differentials between companies. This module introduces and discusses key marketing metrics for evaluating marketing effectiveness, providing insights into and teaching useful skills for managing marketing performance in organisations.
Public opinion matters to governments, to political parties, to pressure groups, to pollsters, and to academics in political science as well as many other areas. It is also interesting. People are more diverse, unpredictable and hard to understand than political parties, trade laws, electoral systems, and so on, and the fickle and elusive nature of public attitudes makes them a challenging but rewarding thing to study. This module is about how we find out what the public think – about policies, priorities, party leaders, even about each other. Since the sample survey is overwhelmingly the dominant method of measuring public opinion, understanding how to conduct surveys and polls is the basis of the module. It will make it easier to understand the material in other modules that draw on survey data, expand the scope of your Masters dissertation (and potentially future doctoral work), and provide skills of use to more or less the full range of employers. Measuring public opinion is a three-step process. First, drawing on the previous module in Political Psychology & Electoral Behaviour, we review the concept of public opinion and the question of whether people care and know enough about politics actually to have opinions and to be able to answer survey questions. The second step is to collect the data. We follow the stages of designing and conducting a survey: writing a questionnaire, deciding who should receive it and how, and fielding the survey. Third, we have to process, clean and analyse those data.
The module provides an overview of relevant topics in mechanical power transmission and methodology of vibration analysis for such mechanical assemblies. The main objective of the module is to learn methods of analysis and design of machines and their components, which are relevant to most industrial applications, including Automotive, Marine and Power Engineering transmissions. This module is taught together with Mechanical Power Transmission and Vibration (MSc). The two modules are mutually exclusive.
The module provides an overview of relevant topics in mechanical power transmission and methodology of vibration analysis for such mechanical assemblies. The main objective of the module is to learn methods of analysis and design of machines and their components, which are relevant to most industrial applications, including Automotive, Marine and Power Engineering transmissions. This module is taught together with ELEC3216 Mechanical Power Transmission and Vibration. ELEC6257 has higher requirements on the desired learning outcomes, which will be assessed by a different coursework assignment. This module is taught together with ELEC3216 Mechanical Power Transmission and Vibration. The two modules are mutually exclusive and you may not take both modules.
This module offers an introduction to the scientific principles and methods of mechanics.
This module builds upon the technical content of the other first year modules and develops skills needed for the professional application of Mechanical Engineering. The ability to solve new challenges through innovation and through application of scientific methods and technical analysis is the heart of Mechanical Engineering. Future Mechanical Engineers will face enormously important and diverse challenges that are difficult to anticipate, and will need to be able to develop their skillset throughout their career. The first part of this module introduces the professional context of Mechanical Engineering and starts the individual process of identifying and developing relevant skills through reflective practice. The second part of this module develops skills concerning the application of engineering analysis to practical mechanical systems. In particular, the ability to frame engineering problems so that relatively simple analysis, practical insight and intuition can be used to generate innovative solutions is developed through a serious of case studies.
This module will help the students to understand the fundamental concepts in Kinematics and Dynamics of multi-body systems. It provides an understanding of the application of simple mathematical models to vibration problems in engineering using different levels of approximation/complexity and some practical experience of vibration measurement and the interpretation of vibration effects. By completing this module an acoustical engineering student will appreciate how simple mechanisms forming a complex machine can be the source of vibration and a mechanical student can appreciate the response of a machine to such excitations. The course assumes knowledge of elementary vector algebra and the concepts of time and partial derivatives. An elementary Physics course covering Newton's laws or course(s) on Statics and Dynamics can be very helpful in understanding the material covered as the course reviews these topics and then applies them to more complex problems. There will be equal emphasis placed on gaining both analytical understanding and insight/intuition on the subject. The material presented in the lectures will emphasize the analytical component of the subject, while with the assignment (through coding and modelling) and the experimental laboratory work will encourage students to see beyond equations. This module will provide a pre-requisite understanding for more advanced topics such as vibration measurement and analysis with numerical tools such as Finite Element Method Analysis and will prepare the students for automotive modules.
