. "Data Science, Data Analysis, Data Mining"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "Spatial-temporal data analysis and data mining (stdm)"@en . . "5" . "Description\nThis module introduces theories and techniques to visualise, model and analyse (big) spatio-temporal data. Students will be introduced to the topics of statistical modelling, data mining and machine learning, and will learn tools and techniques for spatio-temporal analysis, with an emphasis on application to real world problems. The module content covers a range of topics, which include: Exploratory spatio-temporal visualisation, Statistical modelling and forecasting, Clustering and outlier detection , Machine learning techniques (e.g. Support Vector Machines, Random Forests, Artificial Neural Networks and Deep Learning), Space-time multi-agent simulation, and Social media analysis. Lectures are supported by practical sessions, where real data is used to demonstrate the techniques, with applications such as environment, transport, crime and social media analysis. The software packages used include R (http://www.r-project.org/), SaTScan (http://www.satscan.org/), Python and NetLogo (https://ccl.northwestern.edu/netlogo/). The course is suitable for MSc students in GIS, Geospatial Analysis, Spatio-Temporal Analytics, Smart Cities, Computer Science and related subjects.\n\nLearning Outcomes\n\nUnderstand the basic principles and techniques of spatio-temporal analysis and modelling\nBe comfortable working with spatio-temporal data of different types in different application areas\nBe familiar with using R statistical package for space-time analysis, modelling and visualisation\nHave a working knowledge of other software such as SaTScan and NetLogo.\nBe able to apply the tools and techniques they have learned to new datasets." . . "Presential"@en . "FALSE" . . "Master in Remote Sensing and Environmental Mapping"@en . . "https://www.ucl.ac.uk/prospective-students/graduate/taught-degrees/remote-sensing-and-environmental-mapping-msc#course-overview" . "60"^^ . "Presential"@en . "Students develop an all-round knowledge of remote sensing, mapping and data analysis, including fundamental principles, current technological developments and applications to local, regional and global problems. They gain highly developed, marketable practical skills, particularly coding and data analysis, written and other communication skills to enable them to take leading roles in academic, government and industrial sectors"@en . . . . "1"@en . "FALSE" . . "Master"@en . "Thesis" . "14100.00" . "British Pound"@en . "14100.00" . "None" . "Graduates are highly-employable across a wide range of sectors. Recent graduates have been employed in: international space agencies, commercial geospatial and environmental companies; new start-ups using UAVs and satellite data; government agencies; charities and NGOs. The programme is also suitable training for those wishing to undertake a PhD in a quantitative environmental discipline and a number of our graduates have gone on to become leading researchers in the UK and overseas."@en . "1"^^ . "TRUE" . "Downstream"@en . . . . . . . . . . . . . . . .