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{"name":"Python-Fa14","tagline":"CSE Training Workshops in Python, Fall 2014 • DCL L440, 9–11 am","body":"All workshops will be held in L440 Digital Computer Laboratory, an EWS computer laboratory in the basement. There is no sign-up for this series—walk-ins are welcome and encouraged!\r\n\r\n# Setup (Canopy Python and I-Python Notebook)\r\n\r\nFor 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](https://www.enthought.com/products/canopy/), which is installed on your EWS machines already. However, it works best when you are logged in with a Canopy user account, and [free academic accounts](https://store.enthought.com/accounts/login/?next=/licenses/academic/request/) are available and recommended.\r\n\r\nTo load Canopy, please input the following at a terminal window:\r\n\r\n module load canopy\r\n\r\nIn many cases, we will also use [I-Python](http://ipython.org/) notebooks, which are interactive workbooks 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 I-Python notebook interface:\r\n\r\n cd\r\n module load canopy\r\n ipython notebook &\r\n\r\n# [Introduction to Python](#intro)\r\n### Sep. 3, 9:00–11:00 • DCL L440\r\n\r\nThis workshop targets students with little programming experience (in general) or with no prior exposure to Python. We will conduct a hands-on walkthrough of what Python has to offer as a foundation for later tutorials throughout the semester.\r\n\r\nWe will cover the following topics:\r\n\r\n- Variables, functions, sequences, dictionaries\r\n- Libraries and modules\r\n- Loops, logic, and conditionals\r\n- Input/output, files\r\n\r\n(If you don't know what any or all of these are, don't worry! We will explain them.)\r\n\r\n[Link to Lesson](https://github.com/uiuc-cse/python-fa14/blob/gh-pages/notes/intro.md)\r\n\r\n# [Numerical Programming with Python](#numpy)\r\n### Sep. 10, 9:00–11:00 • DCL L440\r\n\r\nThis tutorial focuses on three key packages for scientific and numerical computing with Python: [NumPy](http://www.numpy.org), [SciPy](http://www.scipy.org), and [MatPlotLib](http://matplotlib.org/).\r\n\r\n- [NumPy](http://www.numpy.org) is the foundational numerical module in modern Python (both 2 and 3). NumPy provides the basic array manipulation and mathematical routines that are drawn upon by scientific classes.\r\n\r\n- [SciPy](http://scipy.org/) is a collection of mathematical routines built on top of NumPy. SciPy also provides convenience functions for scientific computing.\r\n\r\n- [MatPlotLib](http://matplotlib.org/) has become the workhorse for plotting in Python. It offers a MATLAB-like syntax coupled with extremely flexible features for displaying data.\r\n\r\n### Lesson Notebooks\r\n\r\nRight-click and _Save As..._ these `ipynb` files to your desktop.\r\n\r\n- [NumPy & SciPy](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/numpy-scipy.ipynb)\r\n\r\n- [MatPlotLib](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/matplotlib.ipynb)\r\n\r\n- [Scientific Coding](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/coding.ipynb)\r\n\r\n- [Numerical Error](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/numerical-error.ipynb)\r\n\r\n### Support Files\r\n\r\n- [`fd-params.cfg`](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/fd-params.cfg)\r\n\r\n- [`heat_eqn_cl.py`](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/heat_eqn_cl.py)\r\n\r\n# [Pandas (Python Data Analysis) Library](#pandas)\r\n### Sep. 17, 9:00–11:00 • DCL L440\r\n\r\nThe [Pandas](http://pandas.pydata.org/) module provides an R-like interface for manipulating and analyzing data sets and their statistics.\r\n\r\n### Lesson Notebook\r\n\r\nRight-click and _Save As..._ this `ipynb` file to your desktop.\r\n\r\n- [Pandas](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/pandas.ipynb)\r\n\r\nTo open it, please open a command line window and enter the following:\r\n\r\n cd ~/Desktop\r\n module load canopy\r\n ipython notebook pandas.ipynb\r\n\r\n### Demonstration File\r\n\r\n- [PMU Data (w/ missing entries)](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/pmu-data.csv)\r\n\r\n# [Object-Oriented & Advanced Programming in Python](#oop)\r\n### Sep. 24, 9:00–11:00 • DCL L440\r\n\r\nWe will introduce modules, classes, and other advanced capabilities of Python, including list comprehension and `lambda` headless functions.\r\n\r\n### Lesson Notebooks\r\n\r\nRight-click and _Save As..._ these `ipynb` files to your desktop.\r\n\r\n- [OOP and Advanced Topics](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/oop-intro.ipynb)\r\n\r\n# [The IPython Environment & Notebooks](#ipython)\r\n### Oct. 1, 9:00–11:00 • DCL L440\r\n\r\nThe [IPython](ipython.org) shell offers a number of useful and convenient enhancements to vanilla Python. The IPython notebook environment gives teachers, learners, and researchers an incredibly flexible and powerful means of interacting with code and data even across several languages and programming conventions.\r\n\r\n### Lesson Notebook\r\n\r\nRight-click and _Save As..._ this `ipynb` file to your desktop.\r\n\r\n- [IPython](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/IPython-1001.ipynb)\r\n\r\nTo open it, please open a command line window and enter the following:\r\n\r\n cd ~/Desktop\r\n module load canopy\r\n ipython notebook pandas.ipynb\r\n\r\n### Demonstration Notebook\r\n\r\n- [MPI in C](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/mpi-c.ipynb)\r\n\r\n# [MPI4Py](#mpi4py)\r\n### Oct. 8, 9:00–11:00 • DCL L440\r\n\r\nParallel programming with MPI has typically been limited to systems languages like C, Fortran, and C++. However, the exciting new MPI4Py module expands MPI functionality to Python without much of the headache of writing with it in C. Come learn MPI4Py through applied short numerical examples and exercises.\r\n\r\nWe will work today on a shared remote server using IPython.\r\n\r\n- Please navigate to [this site](https://ec2-54-210-83-60.compute-1.amazonaws.com:8888/tree) and accept the unsecured certificate.\r\n- The password is `cseuser1`.\r\n- Click on the [`mpi4py.ipynb`](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/mpi4py.ipynb) notebook to open it.\r\n- Select `File`, `Make a copy...` and name it by your netid.\r\n- We'll try it out—this is experimental as well...\r\n\r\n# [PyOpenCL](#pyopencl)\r\n### Oct. 15, 9:00–11:00 • DCL L440\r\n\r\nTaught by Professor [Andreas Kloeckner](http://mathema.tician.de/) of Computer Science.\r\n\r\n# [Machine Learning in Python](#sklearn)\r\n### Oct. 22, 9:00–11:00 • DCL L440\r\n\r\nFind out about basic principles of machine learning and the concomitant power of [`scikit-learn`](http://scikit-learn.org/stable/), a leading machine learning library.\r\n\r\n### Lesson Notebooks\r\n\r\nRight-click and _Save As..._ these `ipynb` files to your desktop.\r\n\r\n- [`scikit-learn`](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/scikit-learn.ipynb)\r\n\r\n# [Debugging in Python (PDB)](#pdb)\r\n### Oct. 29, 9:00–11:00 • DCL L440\r\n\r\nWe will cover exceptions, tracebacks, `pdb`, and other elements of using errors and error handling to your advantage in Python.\r\n\r\n### Lesson Notebooks\r\n\r\nRight-click and _Save As..._ this `ipynb` file to your desktop.\r\n\r\n- [Debugging in Python](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/pdb.ipynb)\r\n\r\n# [C & Fortran Interfaces](#api)\r\n### Nov. 5, 9:00–11:00 • DCL L440\r\n\r\nRight-click and _Save As..._ this `ipynb` file to your desktop.\r\n\r\n- [C & Fortran Interfaces with Python](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/api.ipynb)\r\n\r\nTo open it, please open a command line window and enter the following:\r\n\r\n cd ~/Desktop\r\n module load canopy gcc python\r\n ipython notebook api.ipynb\r\n\r\n# [Numba & Optimization in Python](#numba)\r\n### Nov. 12, 9:00–11:00 • DCL L440\r\n\r\nRight-click and _Save As..._ this `ipynb` file to your desktop.\r\n\r\n- [Optimization with Numba](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/numba.ipynb)\r\n\r\nTo open it, please open a command line window and enter the following:\r\n\r\n cd ~/Desktop\r\n module load canopy\r\n ipython notebook numba.ipynb\r\n\r\n# [Symbolic Manipulation with SymPy](#sympy)\r\n### Nov. 19, 9:00–11:00 • DCL L440\r\n\r\nFor our last workshop of the semester, we will review [SymPy](sympy.org/en/index.html), a symbolic manipulation package comparable to other computer algebra systems such as Maple or Mathematica.\r\n\r\nRight-click and _Save As..._ this `ipynb` file to your desktop.\r\n\r\n- [Computer Algebra with SymPy](https://raw.githubusercontent.com/uiuc-cse/python-fa14/gh-pages/notes/sympy.ipynb)\r\n\r\nTo open it, please open a command line window and enter the following:\r\n\r\n cd ~/Desktop\r\n module load canopy\r\n ipython notebook sympy.ipynb\r\n\r\n# [Solving Problems on Graphs and Meshes with PyDEC](#pydec)\r\n### <font color=\"red\">Canceled</font> • DCL L440\r\n\r\nTaught by Professor [Anil Hirani](http://www.math.uiuc.edu/~hirani/) of Mathematics.\r\n\r\n# Feedback\r\n\r\nPlease let us know what you think about these workshops. This is the first time many of them have been taught and we are anxious to refine them and make them more useful to you. [Link to short survey](https://illinois.edu/fb/sec/3688366)\r\n\r\n# About These Workshops\r\n### Contributors\r\n\r\nNeal Davis and Lakshmi Rao developed these materials. This content is available under a Creative Commons Attribution 3.0 Unported License.\r\n\r\n\r\n\r\n# Contact\r\nIf 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.\r\n","google":"UA-53962544-1","note":"Don't delete this file! It's used internally to help with page regeneration."}