Course summary
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. 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.
Modules
Data Science covers a wide range of specific topics such as: This course aims to equip postgraduate students with core skills in: Data Analytics, Numerical Methods, Theoretical Computer Science, Programming and 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 and High Performance Computing.
Assessment method
Assessment is through a mixture of coursework and examination. The ethos within the Department 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.
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.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
Please note, some of our courses may have additional costs. Please visit the course webpage for further information.
Provider information
Liverpool Hope University
Hope Park
Liverpool
L16 9JD