Day 1
- What is a variable and native python variables
- Lists and Strings: simple variable containers
- Arrays and Dictionary: more complex variable containers
- Control Flow: if, else, and elif statements
- Loops
- Functions
- Reading in files and working with Pandas
- Simple math with Numpy
- Visualizing data with Matplotlib
Day 2
- Slicing and Broadcasting: working effectivly with Numpy
- Pep 8 and docstrings
- Dataframes manipulation: merges and pivot tables
- Classes and objects
- SKlearn module and typical method's usage for machine learning models
- Maps with python (if there is interest)
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this is all the material developed originally for the CUSP NYU 2016-2017 Python Bootcamp and updated for following years through 202 for the SPPA667 Biden School of Public Policy and Administration class 2020. The course is run thorough google colab, so all that the particpants need is a browser enabled device and a computer connection (no package installation required any more)
All the material is designed by me (taking much inspiration a number of internet resources including http://software-carpentry.org/, http://www.practicepython.org/ and many more.
The list of topics I wanted to cover is in bootcampNB.md; entries written in bold were not covered
A single notebook with the code written in class was generated : inclassNB2016.ipynb inclassNB2017.ipynb
I added an exercise to practice for loops, and printing : LoopExercise.ipynb
There is also an exercise to practice for loops, and practice scripting, inline arguments, exception handling, and the time module, but we did not get to most of those topics: printGoodmorningGoodnightExercise.py