Computational Archaeology: GIS, Data Science and Complexity MSc
Postgraduate
In London
Description
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Type
Postgraduate
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Location
London
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Duration
1 Year
Top archaeological researchers and heritage professionals use a raft of computational methods including GIS, data mining, web science, ABM, point-process modelling and network analysis. To impress employers you need the flexibility to learn on the job, leverage open data and program open source software. This MSc draws on UCL's unparalleled concentration of expertise to equip you for future research or significantly enhance your employability.
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About this course
Approximately one third of graduates of the programme have gone on to do PhDs at universities such as Cambridge, Leiden, McGill, Thessaloniki and Washington State. Of these, some continue to pursue GIS and/or spatial analysis techniques as a core research interest, while others use the skills and inferential rigour they acquired during their Master's as a platform for more wide-ranging doctoral research. Several graduates who went on to doctoral research are now lecturers in computational Archaeology: at the University of Cambridge, Queen's University Belfast and the University of Colorado. Other graduates have gone to work in a range of archaeological and non-archaeological organisations worldwide. These include specialist careers in national governmental or heritage organisations, commercial archaeological units, planning departments, utility companies, the defence industry and consultancies.
A minimum of an upper second-class Bachelor's degree in a relevant subject from a UK university or an overseas qualification of an equivalent standard.
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Subjects
- Data Mining
- Network
- Archaeology
- Network Training
- Computational
- GIS
- GIS software
- Archaeological
- Data science
- Complexity MSc
Course programme
Students learn about a wide range of concepts that underpin computational approaches to archaeology and human history. Students become proficient in the archaeological application of both commercial and open source GIS software and learn other practical skills such as programming, data-mining, advanced spatial analysis with R, and agent-based simulation.
Students undertake modules to the value of 180 credits.
The programme consists of two core modules (30 credits), four optional modules (60 credits) and a research dissertation (90 credits).
Core modules- Archaeological Data Science
- Complexity, Space and Human History
- Exploratory Data Analysis in Archaeology
- GIS Approaches to Past Landscapes
- GIS in Archaeology and History
- Remote Sensing in Archaeology
- Spatial Statistics, Network Analysis and Human History
- Web and Mobile GIS (by arrangement with the UCL Department of Civil and Geomatic Engineering
Other options available within the UCL Institute of Archaeology
Dissertation/reportAll students undertake an independent research project which culminates in a dissertation of 15,000 words.
Teaching and learningThe programme is delivered through lectures, tutorials and practical sessions. Careful provision is made to facilitate remote access to software, tutorials, datasets and readings through a combination of dedicated websites and virtual learning environments. Assessment is through essays, practical components, project reports and portfolio, and the research dissertation.
Additional information
Computational Archaeology: GIS, Data Science and Complexity MSc