The FINM August Review is a series of lectures designed for incoming students to prepare for starting with the Financial Mathematics program. The Python Introduction and Review portion is designed to be a refresher or short introduction to the Python programming language. No prior experience is necessary. Even though some incoming students may have extensive prior experience with Python, this review is designed for those with little experience. The aim is to introduce you to what you need to know for the upcoming FINM program. The academic lectures of September Launch and autumn quarter will assume students have mastered the concepts covered throughout August Review, and so it’s critical that all students enter the year with a solid grasp of this material.

• Class:
  • Friday, August 5. 5-8 pm CT on Zoom
  • Friday, August 12. 5-8 pm CT on Zoom
  • Friday, August 19. 5-8 pm CT on Zoom
  • Friday, August 26. 5-8 pm CT on Zoom
• Lecturer: Jeremy Bejarano, [email protected]
• Website: Canvas: https://canvas.uchicago.edu/courses/43730 will be used for grades. Lecture notes will be posted on the course GitHub repo: https://github.com/jmbejara/finm-python-crash-course

Required Software However, the first class will use Google Colaboratory, a free online Python notebook platform that doesn't require any installation. However, each lecture after this will use the following software. Please make sure to install these before then. If you need help installing this software, please ask for help in the discussion section on Canvas.

• Python 3.9, Anaconda Distribution
  • For this class, please download the Anaconda distribution of Python. Be sure to download Python, version 3.9. When you install Anaconda, be sure to install the full Anaconda distribution. The MiniConda version is nice, but I only recommend it for advanced users. Nice instructions for instlaling and using Anaconda can be found (here.)[https://datascience.quantecon.org/introduction/local_install.html]
• The Visual Studio Code text editor
  • A good text editor is important for software development. Some of your classes will use a fully-fledged Integrated Development Environment (IDE) like PyCharm. For this review, I suggest Visual Studio Code. You can download it here: https://code.visualstudio.com/
  • I recommend installing the Anaconda Extension Pack, Jupyter, and Python VS Code extensions.
• Git (optional, but recommended)
  • Although there are many different Git clients and Git GUI's that you could use, I prefer that you install GitKraken. GitKraken bundles a Git Client with its GUI, so you don't need to install multiple pieces of software. GitKraken can be downloaded here.
  • Some classes will use GitHub. GitHub is a website that allows you to store, interactic with, and share your Git repositories online. Please register an account with GitHub if you don't already have one.

Helpful References

A lot of my lecture material will use content from the following helpful books:

• Introduction to Economic Modeling and Data Science, by Thomas J. Sargent and John Stachurski (QuantEcon)
• Note, the whole lectures series on QuantEcon's website is very good: Quantitative Economics, by Thomas J. Sargent and John Stachurski (QuantEcon)
• Python Data Science Handbook, by Jake VanderPlas (PDSH)
• Python for Data Analysis, 2nd Edition, by Wes McKinney (PDA)