Scientific Computing¶
This course will make use of standard Python packages for scientific computing and data science. There are many excellent online notes discussing these tools:
Inferential Thinking: A textbook for Berkeley’s introduction to data science.
The main tools we will use this semester are:
Jupyter Notebooks (https://jupyter.org/)
Literate programming: Interactive documents (written in markdown/LaTeX) explaining the model and the code.
The scipy eco-system for scientific computing: numpy for numerical computation and statistics and pandas for analyzing data.
There is a very useful tutorial on the scipy.stats package.
Visualization: matplotlib, seaborn, and altair.
Tutorial 1 on data visualization in Python
Tutorial 2 on data visualization in Python
Tutorial 3 on data visualization in Python