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.