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Advanced Computer Science

MSc

Mode of study: Full time
Start date: October 2020
Duration of Study: 1 Year

Subject Area: Computer Science, Natural Sciences, Science
FEES (2020/21 academic year): UK/EU - £8,500; International - £15,500

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Programme specifications

Course Overview

The MSc in Advanced Computer Science combines cutting edge techniques with consultancy and experience of working on real company projects to ensure you graduate with the skills that employers demand for a career in the computing and IT sectors across the globe.

The course is designed both for students who have not studied Computer Science before and for students who have a Computer Science background and want to deepen their understanding and develop new techniques and consultancy skills.

Aaron Whittaker, MSc Advanced Computer Science, 2019 graduate

"The cloud computing, programming and web technologies modules are particularly useful to me because they offer skills that parallel the skills required to work in my chosen job sectors." - read more about Aaron Whittaker, MSc Advanced Computer Science, 2019 graduate

James Mitchell, MSc Advanced Computer Science graduate

"I like the idea of working on something big that changes how people interact with things. I would urge anybody considering this programme to take the plunge. I’ve not been disappointed. It was a life changing experience. " - read more about James Mitchell, MSc Advanced Computer Science graduate

Lara Saunders, MSc Student Consultant of the Year

"The MSc in Advanced Computer Science has been hugely beneficial to me, with a variety of interesting modules to help me with my future employment. It has proven to be a challenging but enjoyable course."

About the course

Overview

The MSc in Advanced Computer Science gives the in-depth knowledge and cutting edge skills required for careers where advanced computer systems are used to solve difficult business goals, control complex processes and equipment, and undertake deep and detailed analysis, management, and presentation of data.

You will gain advanced knowledge of the principles and concepts of Internet technologies, software development, and intelligent systems. Alongside this you will develop the practical skills that are necessary for the design, build, deployment and evaluation of distributed information systems and complex, Internet-enabled business applications.

The course covers a wide range of practical skills and theory, from a fast-track programming and systems design course through to advanced data analysis and the use of private cloud hardware. During the course you will learn many techniques, including manipulating large amounts of data, designing and building large applications, leveraging and provisioning cloud services and developing autonomous systems.

The course also teaches you the skills needed to become a technology consultant through the dedicated modules where you are taught and assessed through applying your learning to real-world problems.

In the first part of the programme you will study 8 taught modules over two semesters. In the second part you will have the choice to undertake a formal academic project supervised by academic staff in the School or to take an industry placement. In both options you will apply the skills you have learned during the taught modules. Example companies where students have taken an industry placement include Synectics Solutions, Collective Crunch and Greenhous.

Teaching facilities

You will be taught in dedicated teaching and laboratory space equipped with cutting edge computer systems. We also have a MakerSpace, a multi-purpose research lab equipped with a variety of robots and a Vicon motion-tracking system, a brand-new Gaming Lab and a perception lab with state-of-the-art virtual reality equipment.

Course structure

How the course is taught

You will have formal lectures delivered by academic staff as well as small group tutorial and practical sessions. The courses uses a variety of innovative learning tools and methods working with real clients. For example, in the Distributed Team Project, a group of students work under a project manager and report to them in the same way they will in industry. This gives students experience and skills they can apply directly to their career and jobs in the future.

Small group teaching is central to how to deliver the course and our staff and students are able to very quickly create supportive working relationships.

Each module in the first semester is taught intensively over one week. This means that you will be able to learn the key competencies and skills very quickly. This is particularly important for students who do not have previous experience of studying Computer Science. In the second semester each module is taught every week. You will study more advanced topics and put the key skills you have learned in semester one into practice.

In the second semester, each taught module is taught every week which gives time for students to creatively explore the topics and put their learning into practice.

You will have sixteen hours of lectures and tutorials each week. Alongside this you will expected to work independently on exercises and coursework projects, as well as researching course topics online and in Keele’s University library.

Assessment

The taught modules are mainly assessed by coursework. For example in the Statistical Techniques for Data Analytics: students analyse a large dataset (using, for example, R and/or SQL) and create a report of their findings which is then assessed. Some modules are assessed by examinations. Examinations are normally 2 hours in length where students can not use books and notes are not allowed.

Taught Modules

The list of modules below are offered in the 2018/19 academic year. We expect to offer the same modules in the future but this may change due to staff availability. If the modules change we will inform you during the admissions process.

Core Taught Modules

You will study the following 7 core modules;

User Interaction Design (15 credits – Semester 1): The module provides the knowledge and skills required for a student to be able to work on User Interaction Design based on an evaluated assessment of the factors associated with a given application or user interaction scenario.

Distributed Intelligent Systems (15 credits – Semester 1): This module provides the knowledge and skills required for a student to be able to develop applications to control intelligent systems in a distributed and collaborative context, including the programming of robots or intelligent home appliances (e.g. TV, fridge, etc. equipped with embedded computers).

Statistical Techniques for Data Analytics (15 credits – Semester 1): This module provides the knowledge and skills required for a student to be able to develop applications to store, process, distribute, visualise and analyse large volumes of big data using distributed databases, statistical techniques and machine intelligence methods.

Cloud Computing (15 credits – Semester 2): The module provides the knowledge and skills required for a student to be able to understand the principles of operations of cloud computing and to develop applications for cloud computing environments, e.g. data storage and distribution, software-as-service, interactive content services.

Web Technologies and Security (15 credits – Semester 2): The module provides an understanding of contemporary web technologies used for both server and client side development of web applications, with particular focus on mobile applications, and an understanding of security aspects of such applications and of the defence methods and techniques employed to provide security.

Collaborative Application Development (15 credits – Semester 2): The module places students in a real world scenario requiring cooperation and communication as well as analysis and design skills. This will involve work for a real world client working as a development team.

Research and Consultancy Skills for Consultants (15 credits – Semester 2): The module aims to enhance students' skills and knowledge in preparation for their MSc Project or Industrial Placement and for a successful career as a computing professional.

Optional Modules

All students take one of the following modules. Which module you will take depends on how much computer programming experience you have. This will be decided in a meeting with the Programme Directors at the start of the course.

System Design & Programming (15 credits – Semester 1): This module provides the knowledge and skills required for a student to be able to design software systems and write object oriented programs in an appropriate programming language (e.g. Java, C#).

Research Horizons (15 credits – Semester 1): This module provides the knowledge to the student about a selected computer science research area, and the skills required for development of a mini-project in this area.

Project or Industrial Placement (60 credits)

After you have completed the taught modules you have the choice to undertake a formal academic project supervised by academic staff in the School or to take an industry placement. In both options you will apply the skills you have learned during the taught modules.

The decision about the type of project or placement you will do will be made together with the academic supervisors and will be based on your performance during the taught modules.

Academic Project

The Academic Project assessment is based largely on a substantial final written report of 10,000 - 15,000 words.

You will be able to select your project from a list of projects offered by the academic supervisors. We also encourage students to develop their own projects. Your supervisor who will guide and support you through the project.

Our MSc students have worked with a variety of businesses, including as part of advanced projects related to Keele’s Smart Energy Network Demonstrator. This is a multimillion-pound European research project.

Examples of dissertation projects by previous students include:

Egocentric video summarisation of lifelogging on wearable devices - Philip Mainwaring, 2018
A semi-flexible web API for mobile app data storage - Shamayal Scott, 2018

Industrial Placement

The aim of the Industrial Placement is to give you an opportunity to apply the theoretical and practical content taught during the course in the workplace; solving a problem that relates to the needs of a local business or organisation. You will not only gain valuable computing related work experience but also further develop professionalism and communication skills that employers are looking for.

We find projects through the our existing links with business or you can develop your own project. You will get personal supervision from an academic member of staff in the School and also direction from the industry partner.

Our excellent central location is ideal for industrial projects with over 40 companies situated next to the campus in the Keele Science Park.