| layout | page |
|---|---|
| title | Data Analytics for Earth Sciences |
Instructor: Dr. Gregory Watson
- [Schedule]({{ site.github.url }}/syllabus/data-schedule)
- [Setup]({{ site.github.url }}/syllabus/data-setup)
This course is aimed at providing Earth Scientists with the necessary tools and skills for performing advanced data analytics on geographic data.
Basics:
- Understanding the shell
- Using Git and GitHub
- Best-practice software engineering techniques
Development Environments:
- Jupyter notebooks
- The PyDev development environment
Python:
- Programming with Python 3.5
- Array programming with NumPy
- The Matplotlib 2D plotting library
- Earth science data formats (netcdf, HDF5)
Pandas:
- Introduction to Pandas
- Time series analysis
- Data reshaping
- Geographic data/GIS data manipulation
- Automated analysis
The course will be based on the excellent Software Carpentry curriculum and will incorporate pair-programming and live coding. The course will take a student-centered, active learning, approach to teaching this material. Class will typically consist of a short introductions to programming techniques, followed by hands on computing exercises.