Python-Sp15

CSE Training Workshops in Python, Spring 2015

All workshops will be held in the EWS computer laboratory, L440 Digital Computer Laboratory. There is no sign-up for this series—walk-ins are welcome and encouraged!

L440 DCL is a little tricky to find if you haven't been there before. It's located in the basement, and can be accessed by going down the main staircase in DCL and turning right.

Setup (Python and Jupyter Notebook)

For most of the lessons, we will require outside modules. While several methods for managing your own library of modules exists, we will use Enthought Canopy, which is installed on your EWS machines already. Anaconda is another excellent Python distribution for your home machine.

Introduction to Python

January 28, 10 am–noon

Numerical & Scientific Programming with Python (numpy, scipy)

February 4, 10 am–noon

We will use Jupyter notebooks (formerly I-Python), which are interactive worksheets for code. To open these, please navigate on the command line to your home directory (or wherever your downloaded ipynb files are located), and open the Jupyter notebook interface:

cd
module load canopy
ipython notebook
Lesson Workbooks

Data Analysis with Python (pandas)

February 11, 10 am–noon

This lesson will introduce the basics of the pandas module, a popular library for interacting with data and discovering trends.

We will use Jupyter notebooks (formerly I-Python), which are interactive worksheets for code. To open these, please navigate on the command line to your home directory (or wherever your downloaded ipynb files are located), and open the Jupyter notebook interface:

cd
module load canopy
ipython notebook
Lesson Workbooks

Plotting in Python (matplotlib)

February 18, 10 am–noon

We will discuss MatPlotLib, Seaborn, and principles for making your Python data plots expressive and professional.

Lesson Workbooks

Advanced Programming in Python

February 25, 10 am–noon

We will cover more advanced Python topics such as classes and object-oriented programming, keyword arguments, package installation, and dynamic creation of variables at runtime.

Lesson Workbooks

Machine Learning in Python (scikit-learn)

March 4, 10 am–noon

Using scikit-learn, we will explore machine learning principles such as clustering.

Lesson Workbooks

Error handling in Python (pdb, numerical error)

March 11, 10 am–noon

We will discuss the error tracebacks, debugging, and systematic sources of error.

Lesson Workbooks

Optimizing Numerical Code in Python

March 18, 10 am–noon

There are many ways to speed up your code in Python, including coupling it with C (cython) and Fortran (f2py) and using the popular numba optimization package.

About These Workshops

Contributors

Neal Davis and Lakshmi Rao developed these materials. This content is available under a Creative Commons Attribution 4.0 Unported License.

CC-BY-4.0

Contact

If you have any questions about course availability, concepts, or content, please contact Neal Davis, Training Coördinator for Computational Science & Engineering, at training at cse dot illinois dot edu.