The Audit Data Analytics repository consists of Jupyter Notebooks we created for the Audit Data Analytics Course of the ACA Internal Auditing Programme at the University of St. Gallen (HSG). The content of the notebooks is based on the Python programming language using popular Python libraries, such as NumPy, Pandas, Matplotlib and PyTorch.
Happy Audit Data Analytics!
Further details on the ACA Internal Auditing Programme content und structure can found via the following link (in German). The programm is run by the Chair of Internal Control & Internal Audit and team at the University of St.Gallen (HSG).
Please note, the creation of the distinct notebooks is currently work in progress, so please expect minor bugs as well as some rough edges ;)
We created the following preperatory Jupyter Notebooks that you might want to use to test your the Python installation setup, familiarize yourself with Jupyter Notebooks, and refresh your Python programming skills:
-
Lab P1: Jupyter Test Notebook and Python 101 (Binder:
, Colab:
)
-
Lab P2: Fundamentals of Python Programming (
- Lab 01: Rule-Based Analytics Notebook (
- Lab 02: Benford-Newcomb Law Notebook (
- Lab 03: Autoencoder Neural Networks Notebook (
Installation of the necessary Python packages via pip install -r requirements.txt.
If you have any ideas, questions and remarks, please don' hesitate contact us via: marco (dot) schreyer (at) unisg (dot) ch.