After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
Course Description
This hands-on-course with real-life credit data will teach you how to model credit risk by using logistic regression and decision trees in R. Modeling credit risk for both personal and company loans is of major importance for banks. The probability that a debtor will default is a key component in getting to a measure for credit risk. While other models will be introduced in this course as well, you will learn about two model types that are often used in the credit scoring context; logistic regression and decision trees. You will learn how to use them in this particular context, and how these models are evaluated by banks.
Prerequisites
Curriculum
Course outline
1
Introduction and data preprocessing
This chapter begins with a general introduction to credit risk models. We'll explore a real-life data set, then preprocess the data set such that it's in the appropriate format before applying the credit risk models.
- Introduction and data structure50 XP
- Exploring the credit data100 XP
- Interpreting a CrossTable()50 XP
- Histograms and outliers50 XP
- Histograms100 XP
- Outliers100 XP
- Missing data and coarse classification50 XP
- Deleting missing data100 XP
- Replacing missing data100 XP
- Keeping missing data100 XP
- Data splitting and confusion matrices50 XP
- Splitting the data set100 XP
- Creating a confusion matrix100 XP
2
Logistic regression
Logistic regression is still a widely used method in credit risk modeling. In this chapter, you will learn how to apply logistic regression models on credit data in R.
3
Decision trees
Classification trees are another popular method in the world of credit risk modeling. In this chapter, you will learn how to build classification trees using credit data in R.
4
Evaluating a credit risk model
In this chapter, you'll learn how you can evaluate and compare the results obtained through several credit risk models.
R
Credit Risk Modeling in R
Course
Complete
