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DataCamp – Credit Risk Modeling in R No ratings yet.

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DataCamp Credit Risk Modeling in R

Created/Published/Taught by:
Lore Dirick

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$0.00 - $29.00

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FromĀ DataCamp:

“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 introducing other models in this course as well, we focus on two model types that are often used in the credit scoring context; logistic regression and decision trees. We will teach you how to use them in this particular context, and how these models are evaluated by banks.”

This course consists of four chapters:

  1. Introduction and data preprocessing
  2. Logistic regression
  3. Decision trees
  4. Evaluating a credit risk model

Recommended Prerequisites: none specified; familiarity with R

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