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Programming Resources
Jonah Duckles edited this page Sep 20, 2013
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Here are some resources to help scientists learn about programming. Most of these should be freely available ebooks to researchers at The University of Oklahoma.
- Introduction to Programming Concepts with Case Studies in Python
- A Primer on Scientific Programming with Python
- Python Programming Fundamentals
- Pro Python
- Introduction to Monte Carlo Methods with R
- Introductory Time Series with R
- Functional Data Analysis with R and MATLAB
- Dynamic Linear Models with R
- Applied Spatial Data Analysis with R
- Spatial Data Analysis in Ecology and Agriculture using R
- Forest Analytics with R
- Numerical Ecology with R
- A Practical Guide to ecological modeling using R as a simulation platform
- Introduction to Image Processing Using R
- R and Data Mining
- Biostatistics with R
- Qualitative Comparison Analysis with R
- Advances in Social Science Research Using R
Matlab is a programming language popular amongst engineers for it's built-in matrix mathematics and scientific/engineering toolkits. It is commercial software and does require a license to run. If you're looking for open access to models and code with collaborators all over the world, Python might be a better choice.
- Numerical Computing with Matlab
- Numerical Methods using Matlab
- Matlab Guide
- Matlab Recipes for Earth Science
- Environmental Modeling Using Matlab
- Scientific Programming with MATLAB and Octave
- Scientific Computing with MATLAB
- Bentobox.io - cheat sheet for web technologies.