Course summary

The Master of Data Science (Bioinformatics and Biological Modelling) will provide graduates with quantitative skills in bioinformatics and modelling in molecular biology. It shares a common core with the other Master of Data Science programmes. In addition to the Data Science core, students also take a core module named “Bioinformatics”. There is also an optional module available, “Modelling in Molecular Biology”. The Bioinformatics module explores quantitative tools and methods used to work with biological data, and Modelling in Molecular Biology module explores quantitative modelling tools and methods for exploring metabolic and signalling networks in molecular biology. In your project, you will apply the techniques you have learned from your Data Science modules to a research problem. This course will be equally suitable for those who intend to employ quantitative analysis in their research in molecular biology, or for physical or biological graduates who wish to learn transferrable data and modelling analysis skills in order to enhance their employability in an increasingly competitive job market. All around us, massive amounts of increasingly complex data are being generated and collected, for instance, from mobile devices, cameras, cars, houses, offices, cities, and satellites. Business, research, government, communities, and families can use that data to make informed and rational decisions that lead to better outcomes. It is impossible for any one individual or group of individuals to keep on top of all the relevant data: there is simply far too much. Data science enables us to analyse large amounts of data effectively and efficiently and as a result has become one of the fastest growing career areas. Previously, data science was the province of experts in maths and computer science, but the advent of new techniques and increases in computing power mean that it is now viable for non-experts to learn how to access, clean, analyse, and visualize complex data. There is thus a growing opportunity for those already in possession of knowledge about a particular subject or discipline, and who are therefore able to grasp the full meaning and significance of data in their area, to be able to undertake data analysis intelligently themselves. The combination of primary domain knowledge with an expertise in extracting relevant information from data will give those with this ‘double-threat’ a significant employment advantage. The Master of Data Science suite of programmes is a course with a hard-core of data science, intended to provide Masters-level education rich in the substance of data science for students who hold a first degree that is not highly quantitative, including those in social sciences, the arts and humanities. Introductory modules are designed to bring students with non-technical degrees up to speed with the background necessary for data science. This is done on a need-to-know basis, focusing on understanding in practice rather than abstract theory. Core modules then introduce students to the full range of data science methods, building from elementary techniques to advanced modern methods such as neural networks and deep learning. Optional modules allow students to focus on an area of interest.