Summary:
This course is a CrashProgram (short course) introducing exploratory data analysis. The course is at an introductory technical level. It requires some familiarity with credit risk data (and an ability to open and inspect data files). Step by step we build the knowledge required to perform a comprehensive exploratory data analysis
Prerequisites:
The course can be pursued on a standalone basis. It is advisable to pursue the course after DAT31046 (Risk Data Review) which discusses a review of the data from a data quality validation perspective.
Outcomes:
- We learn the concept and techniques of Exploratory Data Analysis
- Touch upon the issue of bias and how to mitigate it
- Learn about more advanced formats such as HDF
- Basic exploratory analysis using pandas
- Easy visual analysis of association using seaborn
- Contingency tables, WoE and Information Value using pandas, scipy and statsmodels
- We summarize our findings in terms of numerical and graphical results in a mock report written in Markdown format
Course Level and Type:
| Introductory Level | Core Level | Advanced Level | |
| Non-Technical | |||
| Technical | CrashProgram DAT31048 |