Displaying “course” tags
Author: Anonymous
Affiliation: Unidata
Introduction to Python for Atmospheric Science
Introduction to Python for Atmospheric Science & Meteorology. Unidata is working to create a collection of online training materials focused on the use of Python in the atmospheric sciences. While our examples and scenarios may feature Unidata tools and data technologies, our aim is to present a generic set of freely available tools that are generally useful to scientists, educators, and students in the geosciences, broadly defined.
Author: Kerry Key, Ryan Abernathey
Affiliation: Lamont-Doherty Earth Observatory
This book grew out of a course developed at Columbia University called Research Computing in Earth Science. It was written mostly by Ryan Abernathey, with significant contributions from Kerry Key. By separating the book from the class, we hope to create an open-source community resource for python education ...more
This book grew out of a course developed at Columbia University called Research Computing in Earth Science. It was written mostly by Ryan Abernathey, with significant contributions from Kerry Key. By separating the book from the class, we hope to create an open-source community resource for python education in the Earth and Environmental Sciences.
Author: Brian Rose
Affiliation: University of Albany
A hands on approach to climate physics and climate modeling. Fundamental climate processes are introduced through interactive and reproducible Python-based modeling exercises. This JupyterBook serves as a course textbook at the University of Albany.
Author: Earth Lab
Affiliation: University of Colorado Boulder
Earth analytics is an intermediate, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of heterogeneous ‘big scientific data’. This course is designed for graduate students and students participating ...more
Earth analytics is an intermediate, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of heterogeneous ‘big scientific data’. This course is designed for graduate students and students participating in the Earth Data Analytics Professional Certificate.
Author: Earth Lab
Affiliation: University of Colorado Boulder
This site contains open, tutorials and course materials covering topics including data integration, GIS and data intensive science.
Author: eScience Institute
Affiliation: University of Washington
Geohackweek is a 5-day hackweek to be held at the University of Washington eScience Institute. Tutorials from the hackweek are available for everyone to follow (participants and non-participants alike).
Author: Damien Irving, et al.
We believe every researcher should know how to write short programs that clean and analyze data in a reproducible way and how to use version control to keep track of what they have done. But just as some astronomers spend their careers designing telescopes, some researchers focus on building the software ...more
We believe every researcher should know how to write short programs that clean and analyze data in a reproducible way and how to use version control to keep track of what they have done. But just as some astronomers spend their careers designing telescopes, some researchers focus on building the software that makes research possible. People who do this are called research software engineers; the aim of this book is to get you ready for this role by helping you go from writing code for yourself to creating tools that help your entire field advance.
Author: Jovian.ai
"Data Analysis with Python: Zero to Pandas" is a practical and beginner-friendly introduction to data analysis covering the basics of Python, Numpy, Pandas, Data Visualization, and Exploratory Data Analysis.
Author: Jay Gopalakrishnan
Affiliation: Portland State University
In this course, we will have multiple occasions to procure, analyze, and visualize data. We will study mathematical and statistical techniques to discern patterns in complex data. We shall do so in an ecosystem of python computing modules developed by open-source enthusiasts worldwide.
Author: Philip Austin
Affiliation: University of British Columbia
This course teaches radiation and remote sensing, but also covers: how to write clear, documented and tested code that can ingest, manipulate and display data, and how to turn equations into computer algorithms in Python.
Author: The Carpentries
The goal of this lesson is to provide an introduction to core geospatial data concepts. It is intended for learners who have no prior experience working with geospatial data, and as a pre-requisite for the R for Raster and Vector Data lesson . This lesson can be taught in approximately 75 minutes and ...more
The goal of this lesson is to provide an introduction to core geospatial data concepts. It is intended for learners who have no prior experience working with geospatial data, and as a pre-requisite for the R for Raster and Vector Data lesson . This lesson can be taught in approximately 75 minutes and covers the following topics: Introduction to raster and vector data format and attributes, examples of data types commonly stored in raster vs vector format, an introduction to categorical vs continuous raster data and multi-layer rasters, an introduction to the file types and R packages used in the remainder of this workshop, an introduction to coordinate reference systems and the PROJ4 format, and an overview of commonly used programs and applications for working with geospatial data.
Author: Dani Arribas-Bel
Affiliation: University of Liverpool Department of Geography and Planning
A collection of courework repositories for various data science classes taught by Dani Arribas-Bel.
Author:
Affiliation: Data Carpentry
Lesson materials for a one-day workshop on using Python in the atmosphere and ocean sciences. Useful for any geoscientist working with raster (a.k.a. “gridded”) data, the lessons cover packages/tools including conda, xarray, dask and netCDF, as well as best practices including functions, command line ...more
Lesson materials for a one-day workshop on using Python in the atmosphere and ocean sciences. Useful for any geoscientist working with raster (a.k.a. “gridded”) data, the lessons cover packages/tools including conda, xarray, dask and netCDF, as well as best practices including functions, command line programs, defensive programming, provenance tracking and version control via git/GitHub.
atmospheric science cartopy climate science course dask matplotlib numpy xarray
Author: Nikolay Koldunov
Affiliation: Alfred Wegener Institute for Polar and Marine Research
This is a short overview of how Python is used in science and particularly in geosciences targeting people who already know programming (e.g. Matlab).
