PRE-MASTERS IN SCIENCE AND ENGINEERING

Academic English Skills aims to provide thorough training in the language and related academic skills which will enable international students to best achieve their academic potential at university. Our Academic English programme is validated by UK ENIC, the UK government agency responsible for providing information and expert opinion on qualifications and skills worldwide.

You will develop awareness and competency in a range of language-related academic skills, including the processes of academic writing, effective and extensive reading strategies, effective delivery of presentations, and listening to and recording information effectively from lectures. You will also develop the accuracy and range of written and spoken language required to use language effectively and appropriately, with clarity and confidence in an academic context.

Alongside your classes, your studies will be supported by an online learning platform, providing you with a range of tasks and activities specifically designed to develop and extend your language and academic skills outside the classroom and to give you more control over your own learning.

Students will be assessed in all four skills areas: listening, reading, speaking and writing, this is assessed through examinations, coursework and a presentation.

The recommended text for this module are Academic Writing Skills for International Students by Read and English for Academic Study; Reading Course Book for Slaght.

In this module students concentrate on developing the critical skills specific to the reading and writing that will be required in their taught Masters degree programme. The course focuses on developing student criticality, fostering thorough scholarly skills and independent learning through the development of critical note taking and reading skills; the analysis, evaluation and summary of authentic academic texts.

The module will be assessed by notetaking, critical summary and a literature review.

Recommended text for this module are Critical Reading and Writing for Postgraduates by Wallace & Wray and Academic Writing; A Handbook for International Students by Bailey.

This one-term module covers some fundamental techniques in statistics. The module is particularly important because of its huge applicability. The skills studied are used widely across many scientific, business, and social science fields. The module content includes data exploration, correlation and regression, probability distributions and hypothesis testing.

This module is assessed by an invigilated examination.

Recommended texts for this module are Edexcel AS and A Level Mathematics – Statistics & Mechanics Year 2 and Probability and Statistics for Engineering and the Sciences.

_{*Not studied on some Data Science routes} 

This will require them to undertake research in their chosen area of study. The individual project
provides students with a learning experience that will enable them to carry out independent
research. Students are expected to plan, research, and execute their project while developing
skills in critical judgement and independent working, to demonstrate engineering / scientific
competence.

This module is assessed by 1 artefact and 1 proposal of research.

Recommended texts for this module include Glasman-Deal H (2010) Science Research Writing For Non-Native Speakers Of English: A Guide for Non-Native Speakers of English. ICP. ISBN-10: 184816310.

Psychology

• Research Methods for Social Science
• Core Concepts in Psychological Science
• Human Culture and Diversity

Maths/Scientific Computing and Data Analysis/Engineering three term option only

• Advanced Applied Mathematics
• Introduction to Scientific Computing

Data Science

• Mathematics for Economics
• Introduction to Scientific Computing
• Management*
• Research Methods for Social Science*
• Human Culture and Diversity*

^{*Dependant on chosen MDS route.}

Energy Engineering Management

• Advanced Research Methods in Business
• Advanced Applied Mathematics
• Management

Advanced Applied Mathematics

This two-term module is a mathematical methods course and is a review of some key concepts typically studied at undergraduate level by both mathematics and engineering students. The module content includes differential equations, Laplace transforms, Fourier series, Leibnitz theorem, vector calculus and integration.

This module is assessed by two invigilated examinations.

Recommended texts for this module are Advanced Engineering Mathematics 10th Edition and Engineering Mathematics 7th Edition.

Core Concepts in Psychological Science

The module aims to enhance students understanding on a range of topics in Developmental Psychology with an emphasis on cognitive and social development across the life span. Particular attention is paid to the interacting contributions of biological, cognitive and environmental factors. Theory pertaining to all aspects of the course will be presented and critiqued in light of available empirical research. Across the course students will become familiar with different approaches to research and will have to evaluate research. Great emphasis is placed on independent and collaborative student learning. Thus, in addition to key reading, students are expected to study additional material (which will be provided).

This module is assessed by an invigilated examination.

Recommended texts for this module include Baddeley, A., Eysenck, M. W., and Anderson, M. C. (2014). Memory. 3rd Edition. London: Routledge. And Crisp. R. J. and Turner, R. (2014). Essential Social Psychology. 4th Edition. London: SAGE Publications. And Davey, G. C. (2008). Psychopathology: Research, Assessment and Treatment in Clinical Psychology. 3rd edition. Leicester: BPS Blackwell. And Fletcher-Watson, S. and Happé, F. (2019). Autism: A New Introduction to Psychological Theory and Current Debate. 2nd Edition. New York: Routledge.

Introduction to Scientific Computing

The module is designed to allow students to gain a understanding of how computers work and their limitations when carrying out multiple complex calculations and serves as a preparatory course for students wishing to study scientific computing and data analysis at a postgraduate level. The module will introduce the hardware of computing machines as well as modern high-level programming languages commonly used in science, engineering and mathematics. Students will also gain practical experience of writing computer programs using modern high-level languages such as C and Python, and develop skills to write technical and scientific documents to professional standards using LaTeX.

This module is assessed by an assignment and projects.

Recommended texts for this module include Hyde, R. Write Great Code. Volume 1, Understanding the Machine. San Francisco, Ca: No Starch Press, 2004. And Hyde, R. Write Great Code. Volume 2, 2nd Edition: Thinking Low-Level, Writing High-Level. No Starch Press, 2020. And Eijkhout, V. Introduction to High Performance Scientific Computing. Lulu.com, 2010. And Hager, G. and Wellein, G. (2017). Introduction to High Performance Computing for Scientists and Engineers, ser. Chapman & Hall/CRC Computational Science. CRC Press, 2010.  

Advanced Research Methods in Business Management

This module looks to establish academic competency in research methods for use in a business research context. The main aim of this course is to introduce and develop skills relating to research methods. The module will be focussed on developing an understanding of the application, collection and limitation of a variety of techniques related to data and materials relevant to analysis within the area of business.

This module has two summative assessments: an essay and a formal exam.

Recommended reading includes Bryman, A. (2015). Social Research Methods. 5th edn and Saunders, M., Thornhill, P. and Lewis, P. (2018). Research Methods for Business Students. 8th edn.

Maths for Economics

Though economics is technically a social science, students pursuing this field require a firm foundation in mathematics. This one-term module is not a study of economics, but rather a review of the relevant mathematical skills required to aid the study of economics. The module content includes algebra and functions, differentiation, integration, differential equations, matrices, and Lagrange's theorem.

This module is assessed by an invigilated examination.

Recommended texts for this module are Maths for Economics 4th Edition and Essential Mathematics for Economic Analysis 6th Edition.

Research Methods for Social Science

This module provides students with a broad range of research tools and skills required for the social sciences. It aims to equip students with all aspects of the research process and to train them, through active participation, in a wide variety of research techniques.

This module is assessed by a portfolio of tasks.

Recommended texts include Social Research Methods: Fifth edition Oxford University Press (2015) A Bryman.

Human Culture and Diversity

In Human Culture and Diversity, students will investigate fundamental concepts of socio-cultural anthropology through concepts such as culture, kinship, sex and gender, race and ethnicity. Critical analysis and evaluation of ethnographic studies will offer the opportunity for students to address issues of ethnocentrism, cultural relativity, and their implications. Additionally, students will develop the independent research skills needed to succeed in the future.

This module is assessed by an essay.

Recommended texts include ‘Small places, large issues: an introduction to Social and Cultural Anthropology’ (2105) T.H. Eriksen.

• Data Science
• Data Science (Bioinformatics and Biological Modelling)
• Data Science (Digital Humanities)
• Data Science (Earth and Environment)
• Data Science (Health)
• Data Science (Social Analytics)
• Mathematical Sciences
• Scientific Computing and Data Analysis (Astrophysics)
• Scientific Computing and Data Analysis (Earth and Environmental Sciences)
• Scientific Computing and Data Analysis (Financial Technology)
• Scientific Computing and Data Analysis (Robotics and Computer Vision)