Overview
Context of the Credit Risk Modeling in R course at Data Camp
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.
Programme Structure
Chapters
- Logistic regression
- Decision trees
- Evaluating a credit risk model
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
Disciplines
Finance Risk Management Data Science & Big Data View 35 other Short Courses in Risk Management in United StatesAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
PREREQUISITES
- Intermediate R for Finance
Tuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days.
Basic Access: Free; Premium (for individuals): $12.42 per month billed annually; Teams: $25 per month billed annually; Enterprise: Contact sales for pricing