Python Foundations Seminar
Instructor : Dr. Esperanza Huerta
Why should I take this seminar?
This seminar gives you the basic programming foundations needed in data science. Data scientists analyze a great deal of data, always assisted by computers. Data scientists tell computers what to do by coding programs with very detailed instructions.
Before you can engage in data science, you need to know how to interpret, modify, and create computer programs. For this and other seminars, the programming language used is Python.
You should take this seminar if you have no experience programming. If you already know how to program in any other language, you could learn Python on your own.
- Explain programming in data science
- Interpret, modify, and create basic programs in Python
This seminar has three parts. To earn a digital badge you need to complete all three parts: pre-seminar, live seminar, and post-seminar.
You can complete some parts of the seminar, only the live seminar, or only complete the pre or post-seminar, but to earn a digital badge you must complete all three parts.
During the live seminar we interpret, execute, and trace basic Python programs in Google Colaboratory (Colab for short), an online development environment that allows you to write and execute Python code in your browser. The programs created during the seminar use data for electric cars and:
- receive data input from the keyboard and from text files and output data to the screen and to text files
- use basic data types (string, integer, float, and boolean)
- use assignment and basic arithmetic operations
- use unique and divergent (if-then-else) paths of execution
- use loops (for and while)
The materials listed below are materials for students. If you are faculty, please contact us via the Teaching Materials page.
The pre-seminar module contains:
- One note on programming in data science
- A summary of the article “Python has brought computer programming to a vast new audience” published by The Economist on July 19th, 2018. I you want to read the entire article, you need to access it through your library. This article describes the history of Python and its current relevance for data science.
- A note on accessing Google Colaboratory.
The live seminar module contains:
- A pdf of the presentation
- Documents, data, and programs used in the examples about electric cars
- Narratives and data to create python programs to calculate interests