This is a set of notes used for teaching Python to students that have never used Python, or programmed in any language. In a usual semester, it takes approximately 4 weeks (meeting twice a week for an hour) to go through the material, for a freshmen undergraduate class.
- If you would like to get access to the autograded assignments that we have developed, please contact me at
panos@stern.nyu.edu.
- Python for Everybody: Exploring Data In Python 3: This is a textbook for students that are learning Python as their first programming language, with the objective of using programming to handle and analyze data.
- Automate the Boring Stuff using Python: A task-driven textbook that teaches Python by focusing on how to automate various tasks, using programming.
- How To Think Like a Computer Scientist: An interactive guide to programming and Python. The book "Python for Everybody" (listed above) is partially based on this book.
- Learn Python the Hard Way: An introduction to programming and Python. It targets complete beginners. It used a drill-based approach for teaching, which can be tedious at times. Nevertheless, it is considered one of the standard textbooks for learning Python.
- The following Coursera courses Getting Started with Python, Python Data Structures, Using Python to Access Web Data, Using Databases with Python, Capstone: Retrieving, Processing, and Visualizing Data with Python are well-alinged with the objectives of our class.
- Code Academy, Python class: This is a useful interactive tutorial for beginners, who are trying to understand programming in general, and Python in particular
- Google’s Python class
- DataCamp, Intro to Python for Data Science
- DataQuest, Python Basics
- Official Python 2 Tutorial
- Python Tutor
- Useful iPython Notebooks: A wide variety of useful tutorials in iPython Notebooks for a wide variety of topics
- Python for Econometrics
- Quantitative Economics: An introduction to scientific computing using Python, by Thomas J. Sargent and John Stachurski
- http://www.pyschools.com/ [highly recommended]
- http://www.singpath.com/#/paths
- http://learnpython.org/
- http://www.practicepython.org/
- http://www.codeabbey.com/index/task_list
- http://codingbat.com/python
- http://usingpython.com/python-programming-challenges/
- http://www.openbookproject.net/pybiblio/practice/elkner/
- http://www.openbookproject.net/pybiblio/practice/wilson/
- https://github.com/donnemartin/interactive-coding-challenges