Basic R
—
Start learning R in RStudio.

Basic Python
—
Start learning Python with Pandas and Scikit-learn.

Basic git
—
Learn to use git with GitHub in RStudio.

Basic SQL
—
Speak to a database in its native language.

Tidy Data in R
—
Get your data in shape with tidyr & dplyr.

Maps with R
—
Tour R packages that make static and interactive maps.

Tidy Data in Python
—
Get your data in shape with pandas.

Plots in R
—
Craft publication-quality graphics with ggplot2.

Model Formulas
—
Write formulas for linear and GLM regression models in R

Text Mine
—
Carve your texts into structured data.

Data APIs in R
—
Acquire data from websites and APIs using R

Data APIs in Python
—
Acquire data from websites and APIs using Python.

RMarkdown
—
Extend your data pipeline with RMarkdown and Shiny.

Leaflet Maps
—
Make interactive maps in R using the leaflet package.

Shiny Apps
—
Get interactive with the Shiny R package.

Git in the Shell
—
Perform version control from the command line.

Advanced git
—
Learn advanced git techniques with GitHub and RStudio

Advanced Tidyverse
—
Use piped workflows for efficient data cleaning and visualization.

Spatial R Packages
—
Manipulate geospatial data with open source tools.

Vector Operations in R
—
Manipulate vector data.

Raster Operations in R
—
Efficiently analyze raster upon raster.

Open Source Geospatial tools
—
Meet the open source stack underlying geospatial data.

Raster Classification in R
—
Classify your remotely-sensed data.

OPeNDAP with Python
—
Access Land Data Assimilation System models with OPeNDAP.

Relational Databases using SQLite
—
Leverage relational models for organizing and querying data

Relational Databases
—
Make your data safe, scalable and relational.

Basic NetLogo
—
Build agent-based models with a simple graphical interface.

NetLogo Scripting
—
Implement open agent-based models.

Spatial NetLogo
—
Use spatial data in NetLogo ABMs.

Data Documentation & Publishing
—
Package your data and metadata for publication.

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