Enroll Course: https://www.udemy.com/course/formacao-data-science-criacao-de-um-credit-score-com-python/
In the world of finance, understanding and mitigating credit risk is paramount. Banks, credit card companies, and financial institutions worldwide rely on sophisticated methods to assess the likelihood of loan default. One of the most established and effective techniques is credit scoring, and this Udemy course, ‘Credit Score – Módulo 1: Regressão Logística em python’, provides a comprehensive, hands-on introduction to building such a model using Python.
This course is designed for anyone interested in the practical application of data science in finance, specifically how financial institutions develop models to differentiate customer payment profiles. The core of the curriculum revolves around Logistic Regression, the most commonly used technique for credit score model construction. You’ll be guided through the entire pipeline, from understanding and preparing your data to selecting the right variables and fine-tuning your logistic regression model.
What sets this course apart is its practical, ‘hands-on’ approach. You won’t just be learning theory; you’ll be actively building the model alongside the instructor. All the materials, including Python notebooks with all the developed programs, are made available to students, allowing for direct replication and further exploration. The course is entirely in Portuguese, making it an accessible resource for Portuguese-speaking learners.
The fundamental concept of credit scoring is to gather information about a credit applicant and use it to predict their future ability to repay a loan. This information is diverse, encompassing personal details like age, gender, profession, marital status, dependents, address, and income. It also includes public data such as regional default rates, census data, and labor market research. Crucially, it incorporates the consumer’s credit behavior, including outstanding debts, legal actions, credit inquiries, and defaulted payments with creditors.
Credit scoring systems employ mathematical formulas and statistical tools to process this vast array of information, assigning a score that reflects the individual’s credit risk. A higher score generally indicates a lower risk for the lender.
If you’re looking to gain practical skills in financial modeling and understand the inner workings of credit scoring systems, this course is an excellent starting point. Its detailed, didactic approach and focus on practical application make it a valuable investment for aspiring data scientists, financial analysts, or anyone seeking to deepen their knowledge in this critical area.
Enroll Course: https://www.udemy.com/course/formacao-data-science-criacao-de-um-credit-score-com-python/