Integrated Computer Science
Year 5 (Master in Computer Science)
Students select to take the integrated Master in Computer Science (MCS) programme during their Senior Sophister year (typically the deadline is early in October), and as part of this programme spend the second half of Year 4 on an Internship programme. Details of how to apply for this programme are on the Senior Sophister page.
All Year 5 students take a Research Methods module and undertake a significant dissertation project (30 credits). They also select five elective modules from the list below counting for 25 credits some of which are run in Michaelmas term and some in Hilary term.
Core Modules
CS7092 – Dissertation
Module CodeCS7092Module NameDissertationECTS Weighting [1]30 ECTSSemester TaughtSemester 2Module Coordinator/s Assigned Supervisor Module Learning Outcomes On successful completion of the project, the students will be able to: Module Content This research…
CS7CS6 – Research and Innovation
(Semester 1, 5 ECTS) Locate, obtain and critique relevant knowledge and evidence to support innovation and research
Elective Modules
Students in Year 5 choose five of the options below. The form to choose your options can be found at the following link:
CS7CS4 – Machine Learning
(Semester 1, 5 ECTS) Understand what machine learning is and how it works.
CS7DS1 – Data Analytics
(Semester 1 & 2, 10 ECTS) To understand the theory and be able to apply the following techniques
to a set of data.
CS7DS2 – Optimisation Algorithms for Data Analysis
(Semester 2, 5 ECTS) The aims of this module are to give the student skills to model, analyse and solve optimisation problems that arise in data analytics and modern computing and communication systems.
CS7DS3 – Applied Statistical Modelling
(Semester 2, 5 ECTS) This module continues on from CS7CS4 (Machine Learning) with a focus on sampling methods and topical applications.
CS7DS4 – Data Visualisation
(Semester 1, ECTS 5) This module aims to equip the student with the knowledge and tools to visualise data in ways that give insight and understanding.
CS7GV1 – Computer Vision
(Semester 1, 5 ECTS) Image processing, feature detection and matching, image registration, recognition
and segmentation – Motion flow and object tracking in video – Mathematics for
computer vision.
CS7GV2 – Mathematics of Light and Sound
(Semester 1, 5 ECTS) Wave equation and its solution; Maxwell´s equations; Fourier transform and analysis; vibration; mass-spring-damper systems; numerical methods; simulation software.
CS7GV3 – Real-Time Rendering
(Semester 2, 5 ECTS) This module deals with programming for GPU pipeline architectures e.g. geometry,
rasterisation, texturing, fragment / pixel and vertex shaders.
CS7GV4 – Augmented Reality
(Semester 2, 5 ECTS)
This course covers fundamentals and state-of-the-art in augmented reality, as well
as related areas of 3D computer vision and graphics.
CS7GV5 – Real-Time Animation
(Semester 2, 5 ECTS) The aim of this module is to provide students with a deep understanding of the theory and techniques behind real time animation.
CS7GV6 – Computer Graphics
(Semester 1, 5 ECTS) An introduction to computer graphics; problem domain and applications.
CS7IS1 – Knowledge and Data Engineering
(Semester 1, 5 ECTS) The module is designed to explore the management, delivery and inter-operability of knowledge, information and data through knowledge and data engineering.
CS7IS2 – Artificial Intelligence
(Semester 2, 5 ECTS) Appreciate the scope, applications and limitations of artificial intelligence;
CS7IS3 – Information Retrieval and Web Search
(Semester 1, 5 ECTS) Explain the process of content indexing in information retrieval including stop word removal, conflation (stemming, string-comparison), and the language dependency of these methods.
CS7IS4 – Text Analytics
(Semester 2, 5 ECTS) Grasp the scope and limitations of finite state methods in text analysis.
CS7IS5 – Adaptive Applications
(Semester 2, 5 ECTS) User modelling, including Task modelling
User preferences
CS7NS1 – Scalable Computing
(Semester 1, 5 ECTS) This module aims to provide a theoretical and practical understanding of modern scalable systems and architectures, from billions of highly distributed Internet of Things devices, through to present and future concepts, such as Quantum and Nanotech systems.
CS7NS2 – Internet of Things
(Semester 2, 5 ECTS) In this module, students will explore the prevailing vision for an Internet of Things in
a practical, pragmatic manner.
CS7NS3 – Next Generation Networks
(Semester 1, 5 ECTS) This module aims to provide both a theoretical and practical understanding of
modern and next generation networking and systems concepts, principles, practices
and technologies. Contemporary and emerging wired and wireless network systems
are targeted.
CS7NS4 – Urban Computing
(Semester 1, 5 ECTS) This module aims to provide both a theoretical and practical understanding of urban
computing and associated cyber-physical concepts, principles, challenges and
solutions.
CS7NS5 – Security and Privacy
(Semester 2, 5 ECTS) The objectives of this module are: to develop an in-depth understanding of risk, data
privacy, threats and risks of security breaches, an awareness of computer security
(cryptographic) and protocol techniques, and an ability to make appropriate
decisions about securing data.
CS7NS6 – Distributed Systems
(Semester 2, 5 ECTS) This course takes a critical look at some of the architectural issues involved in, and paradigms available for, the construction of large-scale distributed systems such as the infrastructures supporting Google’s search engine or Amazon’s online sales platform. In particular, the course considers how to develop systems that must make trade-offs between performance, consistency, reliability, and availability.
CSP55031 Open Configurable Networks
Module Code CSP55031/EEP55C26 Module Name Open Configurable Networks ECTS Weighting [1] 5 ECTS Semester Taught Semester 1 Module Coordinator/s Marco Ruffini, Shreejith Shanker Module Learning Outcomes On successful completion…
CSU44081 – Entrepreneurship & High-Tech Venture Creation
(Semester 2, 5 ECTS) Explain how high tech venture creation operates, with an emphasis on the processes developed by the Silicon Valley venture community over the past 20 years