University home > Unit and programme catalogues in 2022/23 > Programme catalogue > Faculty of Science > School of Geographical Sciences > Geographic Data Science and Spatial Analytics (MSc) > Specification
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Programme code | 2GEOG002T |
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Programme type | Postgraduate Taught Degree |
Programme director(s) |
Emmanouil Tranos
|
Faculty | Faculty of Science |
School/department | School of Geographical Sciences |
Teaching institution | University of Bristol |
Awarding institution | University of Bristol |
Mode of study | Full Time |
Programme length | 1 years (full time) |
This section sets out why studying this programme is important, both in terms of inspiring you as an individual and in considering the challenges we face. It describes how this degree programme contributes to:
This programme aims to develop the student’s interest in and knowledge and understanding of data science applications in solving geographical problems. The programme will draw upon extensive developments within and outside geography on the use of new sources of big data and data science tools and methods in order to solve spatial problems. This pairing of data, tools and methods will be underpinned by geographical theories and concepts about e.g. cities, neighbourhoods and the inequalities they produce. The programme will enable students to master Geographic Data Science methods and tools and fully understand their foundational epistemological framework. The programme will enable students to generate geographic knowledge using such tools, methods and data, but also critically considering the value and the potential limitations and biases of such data. The graduates of this programme will be able to utilise current state of the art tools and methods and contribute to both geography and data science communities.
The learning outcome statements shown below for your programme have been developed with reference to relevant national subject benchmarks (where they exist), national qualification descriptors (see the Framework for Higher Education Qualifications) and professional body requirements.
Teaching, learning and assessment strategies are listed to show how you will be able to achieve and demonstrate the learning outcomes.
This programme provides opportunities for you to develop and demonstrate knowledge and understanding, qualities, skills and other attributes in the following areas:
Programme Intended Learning Outcomes | Learning/teaching methods and strategies |
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The program delivery will be heavily based on hands-on computer practical employing reproducible coding frameworks, cutting edge and – wherever possible – open source tools. |
Methods of assessment (formative and summative) | |
The assessment strategy for this programme will focus on ensuring students have the requisite skills and independent problem-solving abilities to conduct independent analyses. Each unit will determine its own assessment structure, but the programme embraces innovative assessments including online quizzes, online code assessment tools, group data challenges as well as individual project reports and essays. Generally, assessments will be summative, with formative material provided as comprehension checks within course materials. |
Programme Intended Learning Outcomes | Learning/teaching methods and strategies |
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|
The program delivery will be heavily based on hands-on computer practical employing reproducible coding frameworks, cutting edge and – wherever possible – open source tools. |
Methods of assessment (formative and summative) | |
Emphasis will be placed on assessing not only the final outputs, but also the underpinning code that the students will develop. This generally will involve computational notebooks, which require the submission of code in line with text to describe a full and reproducible process of analysis. We will also encourage the use of interactive and engaging statistical displays (i.e. dashboards or responsive plots) where possible. Generally, assessments will be summative, with formative material provided as comprehension checks within course materials. |
Programme Intended Learning Outcomes | Learning/teaching methods and strategies |
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|
All these tools will be natively incorporated to the teaching material of the programme. |
Methods of assessment (formative and summative) | |
The programme, again, will require this through the submission of computational notebooks, which provide reproducible chains of analysis. These generally will be “computational essays,” which require both explanation and discussion. Keeping with the structure of the program, assessment will generally be summative, with formative workbooks providing comprehension checks alongside other course material. |
This section describes what is expected from you at each level of your programme. This illustrates increasing intellectual standards as you progress through the programme. These levels are mapped against the national level descriptors published by the Quality Assurance Agency.
Level M/7 - Postgraduate Certificate |
An introductory understanding of Geographic Data Science methods, tools and the foundational epistemological framework. Capacity to utilise relevant state-of-the-art methods and tools as well as new sources of data to answer geographical problems. Critical consideration of the value and the potential limitations and biases of such data and tools. |
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Level M/7 - Postgraduate Diploma |
The graduates of this program will be able to utilise cutting edge geographical data science tools and methods and contribute to both geography and data science communities. They will master the use of different data science tools and will be able to develop scientific computing solution for large scale geographical problems. |
Level M/7 - Postgraduate Masters |
On top of the above, the students will be able to effectively contribute to geographic data science group projects and also produce an independent project in a form of a research paper. |
For information on the admissions requirements for this programme please see details in the postgraduate prospectus at http://www.bristol.ac.uk/prospectus/postgraduate/ or contact the relevant academic department.
Students will be encouraged to attend departmental seminars of the Quantitative Spatial Science (QuSS) Research Group as well as other relevant seminars within the University of Bristol.
Programme administrator email geog-pgadmin@bristol.ac.uk. Programme Director Dr Emmanouil Tranos, email: e.tranos@bristol.ac.uk
The following units are must pass for the award of an MSc: GEOGM0046 Mapping and Modelling Geographic Data in R; GEOGM0054 Introduction to Scientific Computing; GEOGM0055 Urban Analytics and City Science
For the definition of must pass units please see the Glossary of Terms from Annex 1 to the Regulations and Code of Practice for Taught Programmes.
Unit Name | Unit Code | Credit Points | Status | |
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Students must take the following units: | ||||
Dissertation: MSc Geographic Data Science and Spatial Analytics | GEOGM0056 | 60 | Mandatory | AYEAR |
Urban Analytics and City Science | GEOGM0055 | 20 | Mandatory | TB-1 |
Data Science and Machine Learning in Geography | GEOGM0053 | 20 | Mandatory | TB-2 |
Mapping and Modelling Geographic Data in R | GEOGM0046 | 20 | Mandatory | TB-2 |
Introduction to Scientific Computing | GEOGM0054 | 20 | Mandatory | TB-1 |
Select 40 credit points from the following: | ||||
Consultancy Project | GEOGM0029 | 20 | Optional | TB-2 |
Qualitative Research Methods in Human Geography | GEOGM0041 | 20 | Optional | TB-2 |
An Introduction to GIS and Remote Sensing for Environmental Policy and Management | GEOGM0013 | 20 | Optional | TB-2 |
Quantifying Climate Risks | GEOGM0045 | 20 | Optional | TB-2 |
Earth System Modeling | GEOGM0030 | 20 | Optional | TB-1 |
Geographic Information Retrieval and Integration | GEOGM0068 | 20 | Optional | TB-1 |
180 |
The pass mark set by the University for any level 7(M) unit is 50 out of 100.
For detailed rules on progression please see the Regulations and Code of Practice for Taught Programmes and the relevant faculty handbook.
All taught masters programmes, unless exempted by Senate, must allow the opportunity for students to exit from the programme with a postgraduate diploma or certificate.
To be awarded a postgraduate diploma, students must have successfully completed 120 credit points, of which 90 must be at level M/7.
To be awarded a postgraduate certificate, students must have successfully completed 60 credit points, of which 40 must be at level M/7.
An award with Merit or Distinction is permitted for postgraduate taught masters, diplomas and certificates, where these are specifically named entry-level qualifications. An award with Merit or Distinction is not permitted for exit awards where students are required to exit the programme on academic grounds but is permitted in designated programmes (as set out in the programme specification) where students choose to withdraw from the intended programme but otherwise achieve the necessary credit points for the exit award.
The classification of the award in relation to the final programme mark is as follows:
Award with Distinction*: at least 65 out of 100 for the taught component overall and, for masters awards, at least 70 out of 100 for the dissertation. **Faculties retain discretion to increase these thresholds.
Award with Merit*: at least 60 out of 100 for the taught component overall and, for masters awards, at least 60 out of 100 for the dissertation. Faculties retain discretion to increase these thresholds.
* The MA in Law has separate regulations for awarding distinction and merit.
** For the award of Distinction, the Faculty of Engineering requires at least 70 out of 100 for the taught component overall and, for masters awards, at least 70 out of 100 for the dissertation.
All taught masters programmes, unless exempted by Senate, must allow the opportunity for students to choose, or be required, to leave at the postgraduate diploma or certificate stage.
To be awarded a postgraduate diploma, students must have successfully completed 120 credit points, of which 90 must be at level M/7.
To be awarded a postgraduate certificate, students must have successfully completed 60 credit points, of which 40 must be at level M/7.
Please note: This specification provides a concise summary of the main features of the programme and the learning outcomes that a typical student might reasonably be expected to achieve and demonstrate if he/she takes full advantage of the learning opportunities that are provided.
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