Course summary

As part of a suite of Data Science Masters this course is targeted at Geographers, Earth and Environmental Scientists who want to learn how to work with managing natural resources and spatio-temporal information flows. These courses are designed to equip students with the key skills and interdisciplinary knowledge to address the challenges of utilising the streams of data produced in modern industry, science and government. The advantage of taking one of these Masters at Durham is that you will be part of a cohort of Masters students who will work together throughout the 12 month course. Included with the Masters course your research project could be carried out in conjunction with a range of partners across industry, regulators and policy-makers building on Durham’s significant strengths in delivering world-leading and world changing research. To equip you for your career all of the students on the suite of Data Science Masters courses share core modules. These shared modules mean you will be carrying out team building activities, present case studies and carry out both formative and summative assessments with students from all four faculties of Durham University ensuring that you learn how to represent not just your own discipline but listen and the integrate views and skills from other disciplines. 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 programme 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.