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Credit Risk Modeling in Python

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5

(3)

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Course Report - Credit Risk Modeling in Python

Course Report

Find detailed report of this course which helps you make an informed decision on its relevance to your learning needs. Find out the course's popularity among Careervira users and the job roles that would find the course relevant for their upskilling here. You can also find how this course compares against similar courses and much more in the course report.

Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Perhaps you have applied for a loan, or a credit card. You are aware that financial companies may process your information before they make a decision. They could lose their business if they approve you for a loan. This course will show you how to prepare credit application data. Machine learning and business principles will be used to reduce risk and improve profitability. Two data sets will be used in order to simulate credit applications. However, the business value must also be considered. Join me to learn more about credit modeling and the expected value.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Introduction to Python for Finance

Intermediate Python

What You Will Learn

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability

In this course, you will learn how to prepare credit application data

You will use two data sets that emulate real credit applications while focusing on business value

Course Instructors

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Michael Crabtree

Data Scientist

Michael is a cross-functional data scientist and big data engineer at Ford. He has created several high-value analytical and data products spanning domains such as manufacturing, purchasing, finance,...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%

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