Pre-Masters in Science and Engineering (2-Terms), Leading to Master of Data Science (Earth and Environment) Study Group - Durham University International Study Centre - Queens Campus, UK

Pre-Masters in Science and Engineering (2-Terms)
The Pre-Masters in Science and Engineering prepares you for a choice of progression degrees at Durham University. You will join the programme for two or three terms, depending on your academic qualifications and level of English language.

You can choose from a range of postgraduate degrees to progress to when you complete this course.

Who is this programme for?

This programme is for international students looking to study a postgraduate science or postgraduate engineering degree at Durham University.

• Choose from a range of degrees within the Department of Engineering, Department of Mathematical Sciences and Department of Psychology.
• Develop your academic knowledge, English language level and study skills needed for progression to your chosen Masters degree.
• Study core modules and designated modules related to your chosen specialism.
• Adjust to the UK education system and explore concepts, terminology and advanced academic writing needed to succeed at postgraduate level.
• Develop practical skills with research projects and laboratory experience.

What will you study?
You will study core modules, which cover general skills, and designated modules that relate to your progression degree. This means your Pre-Masters programme will be tailored to the specific needs of your chosen degree.

Core modules

• Academic English Skills
• Advanced Academic Writing and Critical Reading
• Quantitative Skills
• Extended Research Project

When you complete the Pre-Masters in Science and Engineering, and achieve the required grades, you can progress Master of Data Science (Earth and Environment) at Durham University.

Leading to: Master of Data Science (Earth and Environment)

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.