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Last Update	09/20/2026
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Section 13: Statistical Modeling Deep Dive

5Lessons ·
- 54: Generalized Linear Models in R
  
  Preview
Section 14: Machine Learning in R

5Lessons ·
- 59: Building Models with caret
  
  Preview
- 61: Cross-Validation Techniques in R
  
  Preview
- 62: Random Forests with randomForest Package
  
  Preview
- 63: Gradient Boosting with xgboost in R
  
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Section 22: More Practice Exercises

4Lessons ·
Section 25: R for Business Analytics

4Lessons ·
- 104: Churn Prediction Modeling in R
  
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Section 26: R Text Mining and NLP

4Lessons ·
Section 28: R Deep Learning

3Lessons ·
- 115: Building a Neural Network in R
  
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- 116: Torch for R Basics
  
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Section 29: Advanced Statistical Techniques

5Lessons ·
- 119: Principal Component Analysis in R
  
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- 120: Cluster Analysis: K-Means and Hierarchical in R
  
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Section 35: R Data Cleaning Deep Dive

4Lessons ·
- 140: Handling Outliers Systematically
  
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Section 38: R Ecosystem and Career

4Lessons ·
- 151: R vs Python: When to Choose Which
  
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Section 40: R for Experimentation

3Lessons ·
- 159: Multi-Armed Bandit Simulations in R
  
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Section 45: R for Actuarial and Insurance Analytics

4Lessons ·
- 180: Claims Fraud Detection Modeling
  
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Section 50: More Practice Exercises Round 3

4Lessons ·
Section 52: R Data Governance and Ethics

4Lessons ·
- 208: Bias Detection in Statistical Models
  
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Section 53: More Modeling Practice

5Lessons ·
- 210: Model Interpretability with DALEX
  
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- 211: Feature Importance Analysis in R
  
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- 212: Model Deployment as a Plumber API
  
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- 213: Monitoring Model Drift in Production
  
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- 214: A/B Testing Model Performance Before Deployment
  
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Section 55: R for Sports Analytics

4Lessons ·
- 220: Win Probability Models
  
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