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index.Rmd
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---
pagetitle: "WUR Geoscripting course"
author: "Jan Verbesselt, Dainius Masiliūnas, Arno Timmer"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
rmdformats::html_clean:
title: "WUR Geoscripting course"
highlight: zenburn
---
```{css, echo=FALSE}
@import url("https://netdna.bootstrapcdn.com/bootswatch/3.0.0/simplex/bootstrap.min.css");
.main-container {max-width: none;}
pre {color: inherit; background-color: inherit;}
code[class^="sourceCode"]::before {
content: attr(class);
display: block;
text-align: right;
font-size: 70%;
}
code[class^="sourceCode r"]::before { content: "R Source";}
code[class^="sourceCode python"]::before { content: "Python Source"; }
code[class^="sourceCode bash"]::before { content: "Bash Source"; }
```
# [WUR Geoscripting](https://geoscripting-wur.github.io/) <img src="https://www.wur.nl/upload/854757ab-168f-46d7-b415-f8b501eebaa5_WUR_RGB_standard_2021-site.svg" alt="WUR logo" style="height: 35px;"/>
We recommend refreshing your R and Python knowledge before the course with
#### [DataCamp: Interactive learning ](https://www.datacamp.com/) 
# Week 1
#### [Tutorial 1: Linux & version control](https://geoscripting-wur.github.io/RProjectManagement)
#### [Tutorial 2: Linux terminal & Bash](https://geoscripting-wur.github.io/Intro2Linux)
#### [Tutorial 3: R & Python basics](https://geoscripting-wur.github.io/RPythonBasics/)
# Week 2
#### [Tutorial 4: Package and project management](https://geoscripting-wur.github.io/RProjectManagement/project_management.html)
#### [Tutorial 5: Intro to functions and refresher on R](https://geoscripting-wur.github.io/Scripting4GeoIntro/)
#### Assignment 1
# Week 3
#### [Tutorial 6: Intro to raster](https://geoscripting-wur.github.io/IntroToRaster)
#### [Tutorial 7: Vector - Raster](https://geoscripting-wur.github.io/VectorRaster/)
#### [Project week introduction](https://geoscripting-wur.github.io/ProjectIntro/)
# Week 4
#### [Tutorial 8: Python Environments](https://geoscripting-wur.github.io/pythonEnvs/)
#### [Tutorial 9: Python Programming](https://geoscripting-wur.github.io/PythonProgramming/)
#### Assignment 2
# Week 5
#### [Tutorial 10: Vector data handling with Python](https://geoscripting-wur.github.io/PythonVector/)
#### [Tutorial 11: Raster data handling with Python](https://geoscripting-wur.github.io/PythonRaster/)
# Week 6 & 7
#### Project weeks
# Week 8
#### Self-study for exam
#### Exam
<!-- #### [Tutorial 14: Web harvesting; dealing with twitter data via Python](https://geoscripting-wur.github.io/PythonTwitter/) -->
<!-- #### [Tutorial 15: Webmapping demo](nens.html) -->
# Extra and optional
#### [Intro to vector](https://geoscripting-wur.github.io/IntroToVector/)
#### [Advanced Raster Analysis](https://geoscripting-wur.github.io/AdvancedRasterAnalysis/)
#### [Geoscripting in R: demos](https://geoscripting-wur.github.io/Scripting4Geo/)
#### [Google Earth Engine](https://geoscripting-wur.github.io/Python-GEE/)
<br /><br /><br /><a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-sa/4.0/88x31.png" /></a><br /><span xmlns:dct="http://purl.org/dc/terms/" href="http://purl.org/dc/dcmitype/Text" property="dct:title" rel="dct:type">Geoscripting course material</span> is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International License</a>.