Prerequisities

• Basic understanding of credit risk concepts.
• Familiarity with Excel or spreadsheet tools.
• Introductory knowledge of statistics, data visualization tools (e.g., Power BI, Tableau), and programming
languages like Python or R.

Course Objectives

The course is designed to enhance participants understanding of key concepts in credit risk and their financial
implications. At the end of the course, participants will be able to;
1. Perform exploratory data analysis (EDA) and feature engineering on credit risk data.
2. Develop predictive models to assess and mitigate credit risks.
3. Apply advanced machine learning techniques to enhance credit scoring.
4. Ensure compliance with ethical standards and financial regulations.

Course Outline

• Fundamentals of Credit Risk Analysis
• Exploratory Data Analysis and Visualization
• Predictive Modeling in Credit Risk
• Machine Learning for Credit Risk Analysis
• Advanced Applications and Regulatory Compliance

Duration: 5 days

Target Audience: Risk analysts, credit managers, data professionals in the financial sector