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所在平台: Udemy |
课程主页: https://www.udemy.com/course/developing-credit-risk-scorecard-using-r-programming/
课程评论：没有评论
课程名称：《使用R编程开发信用风险评分卡》 课程概述： 《使用R编程开发信用风险评分卡》课程旨在为参与者提供构建强大信用风险评分卡所需的知识和技能。信用风险评分卡是金融机构用来评估借款人信用worthiness的重要工具，并帮助其做出明智的贷款决策。该课程将引导参与者完成开发信用风险评分卡的整个过程，包括数据预处理、特征工程、模型开发、验证和部署。 课程目标： 完成本课程后，参与者将： - 理解信用风险评估的基本原理，以及评分卡在贷款过程中的作用。 - 熟练使用R编程进行数据操作、可视化和统计分析。 - 学会如何预处理原始信用数据，处理缺失值、异常值和数据不平衡问题。 - 掌握各种特征工程技术，为信用风险建模创建有信息量的变量。 - 获得构建和优化信用风险评估预测模型的实战经验。 - 学习如何使用适当的技术验证信用风险评分卡，以确保准确性和可靠性。 - 理解评分卡实施和监控的最佳实践。 目标受众： 本课程非常适合数据分析师、风险分析师、信用风险专业人士及任何希望使用R编程构建信用风险评分卡的人士。 备注： 参与者需要拥有安装了R和RStudio的计算机，以便充分参与课程中的实操练习和项目。
The "Developing Credit Risk Scorecard using R Programming" course is designed to equip participants with the necessary knowledge and skills to build robust credit risk scorecards using the R programming language. Credit risk scorecards are vital tools used by financial institutions to assess the creditworthiness of borrowers and make informed lending decisions. This course will take participants through the entire process of developing a credit risk scorecard, from data preprocessing and feature engineering to model development, validation, and deployment.Course Objectives: By the end of this course, participants will:Understand the fundamentals of credit risk assessment and the role of scorecards in the lending process.Be proficient in using R programming for data manipulation, visualization, and statistical analysis.Learn how to preprocess raw credit data and handle missing values, outliers, and data imbalances.Master various feature engineering techniques to create informative variables for credit risk modeling.Gain hands-on experience in building and optimizing predictive models for credit risk evaluation.Learn how to validate credit risk scorecards using appropriate techniques to ensure accuracy and reliability.Understand the best practices for scorecard implementation and monitoring.Target Audience: This course is ideal for data analysts, risk analysts, credit risk professionals, and anyone interested in building credit risk scorecards using R programming.Note: Participants should have access to a computer with R and RStudio installed to fully engage in the hands-on exercises and projects throughout the course.
