SCIENCE AND ENGINEERING PRE-MASTERS

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 participation in seminars and 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.

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 critical reading, analysis, evaluation and summary of authentic academic texts.

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; Sampling techniques, Data exploration, Correlation and regression, Probability distributions and Hypothesis testing.

^{*Not studied on some Data Science routes}

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.

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.

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).

Introduction to Scientific Computing

The module is designed to allow students to gain a good 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 provide an introduction to 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, testing and documenting 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.

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.

Maths for Economics

This module is for those who have chosen the Data Science route. Students pursuing this field require a firm foundation in mathematics. This one-term module is not a study of economics, it is 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.

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.

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.

• 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)