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Data Science (Earth and Environmental Analytics) at University of Manchester - UCAS

Course summary

The inexorable rise of the digital world, driven by rapid AI development, has made data scientists more in demand right now than ever before. The advances of analysing big data span beyond the digital and technology industry and are increasingly recognised in the worlds of sport, medicine, space exploration and more. Our MSc Data Science (Earth and Environmental Analytics) course prepares you for a career in this high-demand field. You’ll develop invaluable abilities in key area’s such as:

  • data analysis;
  • project design;
  • computational methods;
  • data stewardship.
See a full list of mandatory and optional course units below. This course focuses on the data techniques and uses that are most relevant to environmental management, with optional course units exploring themes such as pollution control and subsurface geoscience. We welcome applicants from a range of STEM, business and humanities backgrounds, allowing us to create a diverse cohort and enrich discussions around the uses and potential of data. By the end of your studies, you will have developed a highly valued skillset, enhancing your employability across countless sectors such as policy, business, research and more. Previous students have gone on to roles such as data scientists, civil servants, consultants, researchers, entrepreneurs, and in AI.


Entry requirements

High 2:1 honours degree (or overseas equivalent) See application and selection tab. In your application, you should demonstrate aptitude, knowledge and/or interest in three areas: data analytics and/or statistics; computational subjects; and pathway specific requirements. These can be demonstrated by course units taken at undergraduate level and high school level, or professional experience. For this Pathway we would expect applicants to evidence an interest and/or experience in topics related to environmental analysis. Examples are: Working experience in environment-themed topics (e.g. environment, climate, natural ecosystems, human social and economic systems, and health) Experience in working in data science, GIS or environmental based data analysis Evidence of training in environment-themed methods or topics


English language requirements

TestGradeAdditional details
IELTS (Academic)7IELTS Academic test score of 7 overall with no component score below 6.5
TOEFL (iBT)100TOEFL IBT 100 with no score below 22 in each section. TOEFL code for Manchester is 0757

Applicants whose first language is not English should meet the following language requirements: IELTS Academic test score of 7 overall with no component score below 6.5 TOEFL IBT 100 with no score below 22 in each section. TOEFL code for Manchester is 0757 Pre-Sessional English Courses We will consider applicants who do not meet these scores but you may be required to complete a pre-sessional English language course at the University of Manchester prior to the start of the course. To be considered for a pre-sessional English language course for this programme we require the following minimum IELTS (Academic) scores: 6 Week Pre-Sessional Course : IELTS 6.5 overall with 6.0 in each sub-skill 10 Week Pre-sessional Course : IELTS 6.0 overall with 6.0 in three sub-skills, and 5.5 in no more than one sub-skill If you have not yet completed your current academic study and are interested in studying a pre-sessional course, you must hold an IELTS for UKVI (Academic) test certificate to ensure that you are eligible for a separate visa for the English language course.


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

No additional fees or cost information has been supplied for this course, please contact the provider directly.
Data Science (Earth and Environmental Analytics) at University of Manchester - UCAS