Data Science (MSc)

This course is built around the strong skill base of experts in the mathematics and computer science department and to illustrate how new technologies, cutting edge research and novel scientific perspectives can be used together to influence future society in significant and fundamental ways. 

Almost every communication or interaction that takes place in the world today involves a digital interface, whether this is a computer, a laptop, a mobile phone, a smartcard, a camera or a sensor. These interactions are stored as data which can be mined to make better decisions, systems and research.

Recent advances in computational power, machine intelligence and the massive growth of sources of data has led to the development of a new area study: Data Science.

We are no longer looking machine parts or airlines, or stocks and shares data; we are looking at data about people and the world they inhabit. Jake Porway (Executive Director of DataKind) says: “A data scientist is a rare hybrid, a computer scientist with the programming abilities to build software to scrape, combine, and manage data from a variety of sources and a statistician who knows how to derive insights from the information within. S/he combines the skills to create new prototypes with the creativity and thoroughness to ask and answer the deepest questions about the data and what secrets it”. This programme is designed for such people.

Curriculum Overview
The MSc in Data Science aims to equip postgraduate students with core skills in:

• Data Analytics
• Numerical Methods
• Theoretical Computer Science
• Programming
• Applied Computer Science

The students will then undertake a selection of courses such as:

• Big Data & Cloud Computing
• Artificial Intelligence
• Internet of Things
• Mobile Computing
• High Performance Computing

The ethos within the School is to foster enthusiasm for Computer Science and so assessment is largely through project work, giving you the opportunity to explore the subject area and focus on those specific topics that capture your interest. The project entails research and innovation as well as practical industrial applications of the ideas developed during the programme of study.

The dissertation gives you the opportunity to use the skills gained throughout the PG taught provision. Students are expected to specialise in a specific area of research in order to create something new, or to scientifically investigate research questions and independently solve problems in an innovative way. During this practice you should reflect the scientific process and be self-reflective, critical and clear in its explanation of its hypothesis and synthesis of ideas.

Each individual dissertation is worth 60 credits and this is expected to be a student led investigation into a relevant area of Computer Science. A “pool” of topics is available that reflects the research interests of the staff within the department, however, a student can propose their own topic which is then considered by the PG coordinator. Ultimately the research topic needs to be agreed with and approved by the PG coordinator. Students are assigned to a specialist tutor that guides them through the research process. We strongly encourage our students to produce publishable research work, where possible, and thus provide an opportunity to jointly publish their research work with members of the team. Workload allocation is in accordance with the agreed Common Dissertation Policy for allocation and supervision.

Entry Requirements

• A minimum of a Second-Class Honours degree in a relevant discipline (e.g. Data Science, Computer Science, Computing, Science, or engineering-based) awarded by a UK university, or an equivalent higher education qualification.

International Entry Requirements

• Possess a degree from an overseas institution that is judged by the Registrar or Nominee to be equivalent to an upper second class honours degree from a UK University.
• For students whose first language is not English there is a language requirement of IELTS 6.5 overall with 6.0 minimum of all components. In addition to this, we also accept a wide range of International Qualifications, for more information please visit our English Language Requirements page.

Teaching and Research

• The course is delivered by a small, enthusiastic team which prides itself not only on high teaching quality, which has been independently recognised, but also a vibrant research community; in the most recent Research Excellent Framework Exercise, 100% of the Department’s research was deemed to be internationally excellent or recognised. Staff have expertise in many areas such as: Robotics, Bio-mimetic Systems, Bio-inspired Systems, Spiking and Deep Belief Neural Networks, Machine Intelligence, Virtual Reality, Cognitive Mobile Ad-Hoc Network Design and Network Traffic Packet Analysis. Cyber Security, Mathematical Modelling, Computational Mathematics, Nonlinear Dynamical Systems, Wave Propagation, Inverse Problems in Nonhomogeneous Media, Human-Robot Interaction, Computational Motor Control, Haptics, Petri Nets, Biomechanics, Artificial Intelligence, Biomedical Applications, Metaheuristics.
• We have recently opened a purpose-built Robotics Laboratory in our Science Building, equipped with the latest cutting edge technologies including industry-standard software (e.g. Matlab/Simulink, Labview, Visual Studio, 3D Studio Max), Virtual Reality and Augmented Reality interfaces (e.g. Oculus Rift), exotic robots and 3D printing facilities. The laboratory includes robots (Kilobot swarm robots, Aldebaran Nao, i-Sobot, FlowCode Robotic Buggies, Moway Robotic Buggies, Robo Builder, National Instruments robotic platform), embedded systems and devices for physical computing (e.g. Arduino, Makey Makey, Xilinx Zynq, XMOS, Anadigm FPAA), communication modules, wearable and biomedical sensors, marker less motion capture systems, UAVs and drones.

Careers

• This new subject is in high demand: there is an a year on year 13% - 23% increase in demand for Data Scientists with 46% of industry currently having difficultly recruiting staff. It is such a new subject that very few potential Data Scientists have the effective blend of requisite skills in programming, statistics and specific subject knowledge.
• The talent shortage has been evidenced in a number of recent reports: for example the “Big Data Report” from the McKinsey Global Institute (MGI) estimates that the demand for data analysts could exceed the current supply by 140,000 to 190,000 positions by the year 2018. This report illustrates that there are 440,000 to 490,000 total data analyst job positions projected for 2018 with only 300,000 trained analyst to fill those positions. In other words, the demand for big data analysts could be 50 to 60% greater than its projected supply by 2018.
• 26% of companies in the UK are using or planning to use cloud-based big data services, yet only 13% feel they have the skills. Better use of big data could add £216 billion to the UK economy by 2017 (source CEBR).