Brief Description
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Spatial data science is a field of data science focusing on spatial data, thereby incorporating both where and why things happen. Spatial analysis started worldwide with the seminal work of Danie Krige, who worked in mining studies at Wits. Its importance to the South African research community is much wider and these days also include poverty alleviation, meteorology and climate, the environment, ecology, agriculture and epidemiology, to name a few.
To analyse spatially allows the analyst to incorporate the spatial correlation present in many datasets, without which model interpretation may be incorrect. There is a wealth of knowledge on spatial statistics within South Africa, however, the research field of spatial statistics is still relatively young and much expert guidance is required to build the field in terms of research as well as training. Spatial data science has very important applications in the South African context. There is a need to have trained spatial statisticians as well as spatial data scientists across industry and academia.
Course dates:
The course is fully online and self-paced, allowing delegates to begin at any point between 02 May and 31 October. Registration remains open throughout this period, providing delegates with flexibility in scheduling their attendance.
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Learning Outcomes
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After completion of this course, delegates will be able to
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Course Content
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The course covers the following:
The course covers the following topics and practical examples will be done in R and QGIS:
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Entry Requirements
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Course Number: |
P007027 |
Catalogue and Category: |
Other |
Who Should attend: |
Statisticians, GIS experts, practitioners and academics and students with basic knowledge of statistics and who would like to develop their spatial statistics skills for research or industry purposes.
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Delivery Mode: |
Online |
Contact Days: |
0 |