1. Getting started with Python
2. lists and tuples
3. if-else statements
4. input() and the while loop
5. functions
6. classes
7. files
8. pyplot
9. Midterm practice problems
10. Working with CSV and JSON data
11. Vectors and Matrices with numpy
12. Vector processing with numpy
13. Introduction to pandas
14. Preparing for next term

1. Computing a list of prime numbers
2. Is it random?
3. Expression trees
4. Midterm exam
5. Plotting GDP growth vs. population growth
6. Final exam

Syllabus

The syllabus for this course is here.

Anaconda and PyCharm

In preparation for the work we will be doing in the winter and spring, you will need to install the Anaconda Python distribution. This distribution contains the latest version of Python, the Conda package manager, and a large number of useful libraries for data science.

You may also want to install a Python IDE. I recommend the PyCharm IDE.

For details on how to obtain and install Anaconda and PyCharm, please see the Getting started with Python lecture notes.