Global Certificate in Credit Scoring and Machine Learning

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The Global Certificate in Credit Scoring and Machine Learning is a comprehensive course that combines the principles of credit risk assessment with machine learning techniques. This certification is crucial in today's data-driven economy where businesses rely on accurate credit scoring models to make informed decisions.

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ใ“ใฎใ‚ณใƒผใ‚นใซใคใ„ใฆ

With the increasing demand for professionals who can develop and implement robust credit scoring models, this course equips learners with essential skills to advance their careers. It provides a deep understanding of various credit scoring models, machine learning algorithms, and their practical applications in credit risk analysis. Learners will gain hands-on experience in building and implementing credit scoring models using real-world data sets. They will also learn how to interpret results, validate model accuracy, and comply with regulatory requirements. By the end of the course, learners will be able to contribute significantly to their organizations' credit risk management strategies, making them valuable assets in the job market.

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ๅ…ฑๆœ‰ๅฏ่ƒฝใช่จผๆ˜Žๆ›ธ

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้€ฑ2-3ๆ™‚้–“

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ๅพ…ๆฉŸๆœŸ้–“ใชใ—

ใ‚ณใƒผใ‚น่ฉณ็ดฐ

โ€ข Fundamentals of Credit Scoring: Understanding the Basics of Credit Scoring, Credit Scoring Models, Factors Considered in Credit Scoring
โ€ข Machine Learning Concepts: Introduction to Machine Learning, Supervised and Unsupervised Learning, Regression and Classification Algorithms
โ€ข Data Analysis for Credit Scoring: Data Preprocessing, Data Visualization, Exploratory Data Analysis
โ€ข Credit Scoring Models with Machine Learning: Logistic Regression, Decision Trees, Random Forest, Gradient Boosting
โ€ข Model Evaluation and Validation: Split Sampling, Cross-Validation, Performance Metrics
โ€ข Implementing Machine Learning Models: Building Models in Python/R, Model Tuning, Hyperparameter Optimization
โ€ข Bias and Fairness in Credit Scoring: Understanding Bias and Disparate Impact, Techniques to Improve Fairness
โ€ข Regulatory Environment for Credit Scoring: Overview of Regulations, Compliance Considerations for Machine Learning Models

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ใ„ใคใ‚ณใƒผใ‚นใ‚’้–‹ๅง‹ใงใใพใ™ใ‹๏ผŸ

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ใ“ใฎใ‚ณใƒผใ‚นใฎๆ”ฏๆ‰•ใ„ใฎใŸใ‚ใซไผš็คพ็”จใฎ่ซ‹ๆฑ‚ๆ›ธใ‚’ใƒชใ‚ฏใ‚จใ‚นใƒˆใ—ใฆใใ ใ•ใ„ใ€‚

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ใ‚ญใƒฃใƒชใ‚ข่จผๆ˜Žๆ›ธใ‚’ๅ–ๅพ—

ใ‚ตใƒณใƒ—ใƒซ่จผๆ˜Žๆ›ธใฎ่ƒŒๆ™ฏ
GLOBAL CERTIFICATE IN CREDIT SCORING AND MACHINE LEARNING
ใซๆŽˆไธŽใ•ใ‚Œใพใ™
ๅญฆ็ฟ’่€…ๅ
ใงใƒ—ใƒญใ‚ฐใƒฉใƒ ใ‚’ๅฎŒไบ†ใ—ใŸไบบ
London School of International Business (LSIB)
ๆŽˆไธŽๆ—ฅ
05 May 2025
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