(Previously offered: Spring 2018, Fall 2018)
At the completion of this course, students will be able to do the following in the Python 3 programming language:
This is a hands-on finance course, suitable to masters students or advanced undergraduates. Students are expected to have taken previous classes in:
where the course numberings reflect codings for undergraduate LSU courses. These courses reflect the bare minimum amount of prerequisite knowledge, and students will benefit from having taken other courses with some exposure to data analysis.
In contrast to the above accounting, finance, math, and statistics prerequisites, no prior programming experience is required.
This class applies financial concepts to real-world data using Python. Both computation and presentation are emphasized skills in this class, and these two features are joined together in the phenomenal Jupyter notebook system. Basically, a Jupyter notebook is a file that runs within your web browser and is capable of incorporating formatted text, live Python code, and beautifully rendered equations all within one document. This class runs notebooks on cocalc.com, a teaching resource that simplifies distribution of course materials and collection of assignments. Because computation is handled on a web server, there are no specific laptop requirements for the class. However, students are expected to bring a laptop to each class so that they may code along with the lecture.
The computing environment for this course has evolved over time. Virtual machines (VMs) hosted by Azure/AWS had more complicated frameworks for distributing course materials and collecting assignments. A kubernetes implementation (e.g. z2jh) solves some of this, but does not include the chat system or other bells and whistles offered by cocalc.
|Language||Application||Duration of Experience|
|Python||web scraping (BeautifulSoup, Selenium), textual analysis (NLTK, spaCy)||8+ years|
|Stata||applied microeconometric modeling||8+ years|
|SAS||data manipulation and analysis||8+ years|
|R||statistical modeling||3+ years|
|Matlab||data analysis and statistical modeling||2+ years|
|Machine Learning||hobby projects||1+ years|