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.

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.

Engineering

• Computational Maths
• Advanced Applied Mathematics
• Lab Skills and Experimental Design (three-term only)

Psychology

• Research Methods in Psychology
• Core Concepts in Psychological Science
• Lab Skills and Experimental Design (three-term only)

Maths/Scientific Computing and Data Analysis (three term option only)

• Advanced Applied Mathematics
• C++ Programming

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.

Computational Mathematics

The main aim of the course is to equip the students with basic understanding of computational mathematics. The course includes detailed study of mathematical modelling techniques that can be used across wide range of practical problems in applied mathematics, and engineering. The course will provide a base for more advance applied mathematics and engineering courses.The course will not only cover the theoretical aspects of computational mathematics, but will also include practical examples using a suitable computer software package.

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).

C++ Programming

The aim of this module is to equip students with a solid understanding of machine organisation in the context of C/C++. The module is built on the foundation that good code is efficient code and before the individual can write truly efficient code, they must understand exactly how computer systems execute programs and how abstractions in programming languages map to the machine’s low level hardware. Focus will be given to learning how a computer represents data, so that the student will understand how high-level language data types translates to the machine level.
In addition, by understanding how a CPU executes machine instructions, students will learn about the computational cost of each operation. As such, students will study how a CPU operates, with a view to writing efficient code that works the way the machine does. 
This module will also include how different types of data should be organised so that it can be accessed efficiently by a machine, including understanding how the machine represents numbers and other data structures. At the end of this module  students should have a greater understanding of how to best use the memory hierarchy of a machine to produce, fast, efficient computer programs.

This two-term module covers some key concepts in the field of pure mathematics called analysis. The central object of study in analysis is the limit, which further extends to the notions of convergence, continuity, differentiation and integrability. The module content includes; Proof and logic, Sets, Relations and functions, Differentiation, Integration, The real number system, Limits and continuity and Sequences and series.

Research Methods in Psychology

This module provides students with a broad range of research tools used in Psychology. 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.

• 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)