This course is a CrashProgram (short course) introducing exploratory data analysis.
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.
Step by step we build the knowledge required to perform a comprehensive exploratory data analysis
- 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:
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).
|Introductory Level||Core Level||Advanced Level|
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