We are pleased to announce the addition of a new course – Credit Risk Modelling in R – to our growing library of courses on Data Science for Finance Professionals.
Course: Credit Risk Modelling
Learn to model credit risk using statistical models such as logistic regression and decision trees with real-life data.
In this course, our objective is to learn how to build these credit risk models. While credit risk arises in almost all business lines for a bank, our focus will be on the credit risk involved in the personal and corporate loans which are of major importance to banks.
We will learn credit risk modeling using case studies. Specifically, we will use two case studies starting with a simpler one using which we will learn the methodology and important concepts and techniques.
If you have a monthly or yearly subscription for Finance Train, you will already have access to this course in your course bundle. If not, then you can purchase this course independently for a price of $19 or you can take our monthly subscription that gives you access to all our courses.
The Finance Train’s Financial Data Scientist program is designed to be a monthly subscription program where new courses are added every week to help you keep yourself up-to-date with the latest in financial data science. The courses focus on teaching programming languages such as R and Python. Along with this it also includes courses covering concepts in quantitative methods and various finance topics. All the tutorial examples, data sets used, and projects are focused on the application of data science in the finance field.