Department of Computer Science
  1. Adaptive Computing Systems
  2. Machine Learning
  3. giCentre
  4. Human Computer Interaction Design
  5. Software Reliability
  6. Research Ethics
  7. Data Science
Department of Computer Science

Data Science - an emerging discipline

We live in a society which generates data at an unprecedented rate.

Nearly all of our digital and physical activities carry a data footprint. Everyday devices such as phones and watches, our activities on social media or on the web, sophisticated imaging devices in genomics and medicine, sensors, cameras and even travel cards within our "smarter" cities, or machinery in production industries are just some prominent examples of where data is generated.

Great value and knowledge resides in these data sources, waiting to be harnessed to help us to better understand society, to improve services, to increase efficiency, and foster scientific discovery that helps advance technology.

However, the sheer amount and complexity of this data brings with it itself several challenges requiring a concerted effort from various fields of research to develop techniques, methods, and digital platforms to enable us to extract valuable and useful knowledge from data. This tremendous potential in data-intensive applications and the challenges waiting to be solved, has led to the emergence of Data Science as a field of study.

What is Data Science?

Data Science lies at the intersection of several fields of research as is therefore a highly cross-disciplinary area of study bringing together knowledge and research from statistics, applied mathematics and various sub-fields of computer science such as machine learning, artificial intelligence, data mining, data visualisation and data management to name a few.

Data Science strives to develop innovative solutions that enable the extraction of knowledge from data sources with different characteristics and of various levels of complexity and size.

The discipline looks for comprehensive solutions to support what is called the life-cycle of data-intensive systems from the collection and efficient storage of the data to the advanced analysis and modelling phase with the final goal of extracting information to build automated solutions to help us make decisions effectively and to foster novel discovery.

With data getting increasingly woven into our everyday life, into how businesses operate, and into how science is carried out, the need for creative computational solutions will be on the rise for decades to come. Researchers and practitioners in this exciting field will be the designers and drivers of this data-intensive transformation our society is already going through and will carry great responsibility in shaping a better future.

Data Science as a profession

There is currently a very high demand in the industry for data scientist skills - certain reports indicate that the demand for data scientists in the UK has grown more than ten-fold in the past five years.

Given the growing importance and applicability of data-intensive systems in almost all strands of business and research, this high demand in data scientist skills is likely to grow and sustain its levels for a prolonged period of time.

As data scientists, you could expect to find yourself at various roles within a wide range of businesses and governmental organisations working in areas such as health, retail, transport, manufacturing, media or digital technologies to name a few.

The roles could be within technology companies developing solutions for other industries, or within the in-house data science teams of companies that put data at the core of their business. Depending on your interest and focus, you can choose to be on various roles: developing effective infrastructure for data management, developing algorithms and computational tools to analyse and model data, or designing and developing strategies and policies together with domain experts.

Alternatively, you could choose to take an academic route and continue studying further in developing novel techniques and approaches on theoretical and applied aspects of data science. Given the wide applicability of data scientist skills, you could expect to work collaboratively as part of interdisciplinary teams combating grand research challenges.

Data Science at City

Data Science education at City builds on the expertise and the research excellence within the Computer Science Department, in particular in the areas of machine learning and visualisation.

Our study brings together foundational computer scientists skills such as algorithmic thinking and programming with fundamental data scientist skills such as statistical analysis, machine learning, artificial intelligence, big data, and visual analytics. This is a powerful combination - data scientists having both of these skills will not only master using existing solutions but will also be capable of building innovative data science solutions tailored for the needs of the application at hand.

Our four-year undergraduate MSci Data Science programme builds on the success and reputation of our MSc in Data Science course that has been already running for a number of years.

The MSci programme distinguishes itself from the MSc with its focus on building strong foundations in Computer Science as well as equipping students with comprehensive Data Science skills. In addition to data science specific know-how, MSci students will learn distinguishing computer science skills such as software design and development, working as part of a development team, and an understanding of professional issues in information technologies.