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Please note that this page does not hosts or makes available any of the listed filenames. You
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| [CourseClub.Me].url |
48B |
| [CourseClub.Me].url |
48B |
| [CourseClub.Me].url |
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| [CourseClub.Me].url |
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| [CourseClub.Me].url |
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| [DesireCourse.Net].url |
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| [DesireCourse.Net].url |
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| [DesireCourse.Net].url |
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| [DesireCourse.Net].url |
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| [DesireCourse.Net].url |
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| 1.1 Calculating expected loss with comments.html |
207B |
| 1.1 Calculating probability of default for a single customer with comments.html |
187B |
| 1.1 EAD model estimation and interpretation with comments.html |
202B |
| 1.1 Importing the data into Python with comments.html |
188B |
| 1.1 LCDataDictionary.xlsx |
19.60KB |
| 1.1 LGD and EAD models independent variables with comments.html |
202B |
| 1.1 LGD model preparing the inputs with comments.html |
202B |
| 1.1 Out-of-sample validation (test).html |
165B |
| 1.2 Calculating expected loss.html |
185B |
| 1.2 Calculating probability of default for a single customer.html |
165B |
| 1.2 Data preparation with comments.html |
188B |
| 1.2 EAD model estimation and interpretation.html |
180B |
| 1.2 Importing the data into Python.html |
166B |
| 1.2 LGD and EAD models independent variables..html |
180B |
| 1.2 loan_data_2007_2014_preprocessed.csv.html |
144B |
| 1.2 Out-of-sample validation (test) with comments.html |
187B |
| 1.3 Data Preparation.html |
166B |
| 1.3 LGD model preparing the inputs.html |
180B |
| 1.3 loan_data_2007_2014_preprocessed.csv.html |
144B |
| 1.4 Dataset for the course.html |
131B |
| 1. Calculating expected loss.mp4 |
126.70MB |
| 1. Calculating expected loss.srt |
20.20KB |
| 1. Calculating probability of default for a single customer.mp4 |
39.75MB |
| 1. Calculating probability of default for a single customer.srt |
5.55KB |
| 1. EAD model estimation and interpretation.mp4 |
48.01MB |
| 1. EAD model estimation and interpretation.srt |
8.06KB |
| 1. How is the PD model going to look like.mp4 |
37.59MB |
| 1. How is the PD model going to look like.srt |
5.28KB |
| 1. Importing the data into Python.mp4 |
32.86MB |
| 1. Importing the data into Python.srt |
5.60KB |
| 1. LGD and EAD models independent variables..mp4 |
50.03MB |
| 1. LGD and EAD models independent variables..srt |
8.29KB |
| 1. LGD model preparing the inputs.mp4 |
24.24MB |
| 1. LGD model preparing the inputs.srt |
4.39KB |
| 1. Our example consumer loans. A first look at the dataset.mp4 |
36.70MB |
| 1. Our example consumer loans. A first look at the dataset.srt |
3.99KB |
| 1. Out-of-sample validation (test).mp4 |
52.43MB |
| 1. Out-of-sample validation (test).srt |
8.79KB |
| 1. PD model monitoring via assessing population stability.mp4 |
39.03MB |
| 1. PD model monitoring via assessing population stability.srt |
6.85KB |
| 1. Setting up the environment - Do not skip, please!.mp4 |
5.99MB |
| 1. Setting up the environment - Do not skip, please!.srt |
1.30KB |
| 1. The PD model. Logistic regression with dummy variables.mp4 |
60.51MB |
| 1. The PD model. Logistic regression with dummy variables.srt |
10.55KB |
| 1. What does the course cover.mp4 |
72.92MB |
| 1. What does the course cover.srt |
7.98KB |
| 10.1 Check for missing values and clean the data Homework - Solution.html |
166B |
| 10.1 LGD model combining stage 1 and stage 2.html |
180B |
| 10.2 Check for missing values and clean the data Homework - Solution with comments.html |
188B |
| 10.2 LGD model combining stage 1 and stage 2 with comments.html |
202B |
| 10. Check for missing values and clean Homework.html |
668B |
| 10. Data preparation. Splitting data.html |
141B |
| 10. Different facility types (asset classes) and credit risk modeling approaches.mp4 |
104.45MB |
| 10. Different facility types (asset classes) and credit risk modeling approaches.srt |
11.96KB |
| 10. LGD model combining stage 1 and stage 2.mp4 |
23.97MB |
| 10. LGD model combining stage 1 and stage 2.srt |
4.23KB |
| 10. Setting cut-offs. Homework.html |
957B |
| 11.1 Data preparation. An example with comments.html |
188B |
| 11.1 PD model complete with comments.html |
177B |
| 11.2 Data preparation. An example.html |
166B |
| 11.2 PD model complete.html |
155B |
| 11. Data preparation. An example.mp4 |
49.90MB |
| 11. Data preparation. An example.srt |
11.11KB |
| 11. Different facility types (asset classes) and credit risk modeling approaches.html |
141B |
| 11. LGD model combining stage 1 and stage 2.html |
141B |
| 11. PD model logistic regression notebooks.html |
73B |
| 12.1 Dataset with new data (loan_data_2015.csv).html |
126B |
| 12. Data preparation. An example.html |
141B |
| 12. Homework building an updated LGD model.html |
1.43KB |
| 13.1 Data preparation. Preprocessing discrete variables automating calculations.html |
166B |
| 13.2 Data preparation. Preprocessing discrete variables automating calculations with comments.html |
188B |
| 13. Data preparation. Preprocessing discrete variables automating calculations.mp4 |
43.72MB |
| 13. Data preparation. Preprocessing discrete variables automating calculations.srt |
7.80KB |
| 14. Data preparation. Preprocessing discrete variables automating calculations.html |
141B |
| 15.1 Data preparation. Preprocessing discrete variables visualizing results with comments.html |
188B |
| 15.2 Data preparation. Preprocessing discrete variables visualizing results.html |
166B |
| 15. Data preparation. Preprocessing discrete variables visualizing results.mp4 |
66.35MB |
| 15. Data preparation. Preprocessing discrete variables visualizing results.srt |
12.91KB |
| 16.1 Data preparation. Preprocessing discrete variables creating dummies (Part 1) with comments.html |
188B |
| 16.2 Data preparation. Preprocessing discrete variables creating dummies (Part 1).html |
166B |
| 16. Data preparation. Preprocessing discrete variables creating dummies (Part 1).mp4 |
49.71MB |
| 16. Data preparation. Preprocessing discrete variables creating dummies (Part 1).srt |
9.52KB |
| 17. Data preparation. Preprocessing discrete variables creating dummies (Part 1).html |
141B |
| 18.1 Data preparation. Preprocessing discrete variables creating dummies (Part 2).html |
167B |
| 18.2 Data preparation. Preprocessing discrete variables creating dummies (Part 2) with comments.html |
189B |
| 18. Data preparation. Preprocessing discrete variables creating dummies (Part 2).mp4 |
93.29MB |
| 18. Data preparation. Preprocessing discrete variables creating dummies (Part 2).srt |
15.06KB |
| 19. Data preparation. Preprocessing discrete variables creating dummies (Part 2).html |
141B |
| 2.1 Creating a scorecard with comments.html |
187B |
| 2.1 LGD model testing the model with comments.html |
202B |
| 2.2 Creating a scorecard.html |
165B |
| 2.2 LGD model testing the model.html |
180B |
| 2. Calculating expected loss.html |
141B |
| 2. Creating a scorecard.mp4 |
97.45MB |
| 2. Creating a scorecard.srt |
16.75KB |
| 2. EAD model estimation and interpretation.html |
141B |
| 2. How is the PD model going to look like.html |
141B |
| 2. Importing the data into Python.html |
141B |
| 2. LGD and EAD models independent variables.html |
141B |
| 2. LGD model testing the model.mp4 |
42.67MB |
| 2. LGD model testing the model.srt |
6.84KB |
| 2. Our example consumer loans. A first look at the dataset.html |
141B |
| 2. Out-of-sample validation (test).html |
141B |
| 2. PD model monitoring via assessing population stability.html |
141B |
| 2. The PD model. Logistic regression with dummy variables.html |
141B |
| 2. What is credit risk and why is it important.mp4 |
58.17MB |
| 2. What is credit risk and why is it important.srt |
6.09KB |
| 2. Why Python and why Jupyter.mp4 |
29.24MB |
| 2. Why Python and why Jupyter.srt |
6.43KB |
| 20.1 Data preparation. Preprocessing discrete variables. Homework with comments.html |
189B |
| 20.2 Data preparation. Preprocessing discrete variables Homework - Soluton.html |
167B |
| 20. Data preparation. Preprocessing discrete variables. Homework..html |
1.23KB |
| 21.1 Data preparation. Preprocessing continuous variables Automating calculations with comments.html |
189B |
| 21.2 Data preparation. Preprocessing continuous variables Automating calculations.html |
167B |
| 21. Data preparation. Preprocessing continuous variables Automating calculations.mp4 |
45.06MB |
| 21. Data preparation. Preprocessing continuous variables Automating calculations.srt |
6.63KB |
| 22. Data preparation. Preprocessing continuous variables Automating calculations.html |
141B |
| 23.1 Data preparation. Preprocessing continuous variables creating dummies (Part 1).html |
167B |
| 23.2 Data preparation. Preprocessing continuous variables creating dummies (Part 1) with comments.html |
189B |
| 23. Data preparation. Preprocessing continuous variables creating dummies (Part 1).mp4 |
44.03MB |
| 23. Data preparation. Preprocessing continuous variables creating dummies (Part 1).srt |
9.83KB |
| 24. Data preparation. Preprocessing continuous variables creating dummies (Part 1).html |
141B |
| 25.1 Data preparation. Preprocessing continuous variables creating dummies (Part 2).html |
167B |
| 25.2 Data preparation. Preprocessing continuous variables creating dummies (Part 2) with comments.html |
189B |
| 25. Data preparation. Preprocessing continuous variables creating dummies (Part 2).mp4 |
111.79MB |
| 25. Data preparation. Preprocessing continuous variables creating dummies (Part 2).srt |
19.37KB |
| 26. Data preparation. Preprocessing continuous variables creating dummies (Part 2).html |
141B |
| 27.1 Data preparation. Preprocessing continuous variables creating dummies. Homework with comments.html |
189B |
| 27.2 Data preparation. Preprocessing continuous variables creating dummies. Homework.html |
167B |
| 27. Data preparation. Preprocessing continuous variables creating dummies. Homework.html |
1.90KB |
| 28.1 Data preparation. Preprocessing continuous variables creating dummies (Part 3).html |
167B |
| 28.2 Data preparation. Preprocessing continuous variables creating dummies (Part 3) with comments.html |
189B |
| 28. Data preparation. Preprocessing continuous variables creating dummies (Part 3).mp4 |
100.95MB |
| 28. Data preparation. Preprocessing continuous variables creating dummies (Part 3).srt |
16.86KB |
| 29. Data preparation. Preprocessing continuous variables creating dummies (Part 3).html |
141B |
| 3.1 Calculating expected loss complete notebook with comments.html |
207B |
| 3.1 Dataset for the course.html |
131B |
| 3.1 Dependent variable GoodBad.html |
166B |
| 3.1 EAD model validation.html |
180B |
| 3.1 Evaluation of model performance accuracy and area under the curve (AUC) with comments.html |
187B |
| 3.1 LGD and EAD models dependent variables.html |
180B |
| 3.1 Loading the data and selecting the features.html |
165B |
| 3.1 Preprocessing few continuous variables with comments.html |
188B |
| 3.2 Calculating expected loss complete notebook.html |
185B |
| 3.2 Dependent variable GoodBad with comments.html |
188B |
| 3.2 EAD model validation with comments.html |
202B |
| 3.2 Evaluation of model performance accuracy and area under the curve (AUC).html |
165B |
| 3.2 LGD and EAD models dependent variables with comments.html |
202B |
| 3.2 Loading the data and selecting the features with comments.html |
187B |
| 3.2 Preprocessing few continuous variables.html |
166B |
| 3. Creating a scorecard.html |
141B |
| 3. Dependent variable Good Bad (default) definition.mp4 |
38.97MB |
| 3. Dependent variable Good Bad (default) definition.srt |
7.13KB |
| 3. Dependent variables and independent variables.mp4 |
65.88MB |
| 3. Dependent variables and independent variables.srt |
8.02KB |
| 3. EAD model validation.mp4 |
29.89MB |
| 3. EAD model validation.srt |
5.65KB |
| 3. Evaluation of model performance accuracy and area under the curve (AUC).mp4 |
75.90MB |
| 3. Evaluation of model performance accuracy and area under the curve (AUC).srt |
14.40KB |
| 3. Homework calculate expected loss on more recent data.html |
974B |
| 3. Installing Anaconda.mp4 |
29.26MB |
| 3. Installing Anaconda.srt |
4.55KB |
| 3. LGD and EAD models dependent variables.mp4 |
40.31MB |
| 3. LGD and EAD models dependent variables.srt |
6.89KB |
| 3. LGD model testing the model.html |
141B |
| 3. Loading the data and selecting the features.mp4 |
43.26MB |
| 3. Loading the data and selecting the features.srt |
7.36KB |
| 3. Population stability index preprocessing.mp4 |
105.25MB |
| 3. Population stability index preprocessing.srt |
14.75KB |
| 3. Preprocessing few continuous variables.mp4 |
83.70MB |
| 3. Preprocessing few continuous variables.srt |
17.31KB |
| 3. What is credit risk and why is it important.html |
141B |
| 30.1 Data preparation. Preprocessing continuous variables creating dummies Homework - Solution.html |
167B |
| 30.2 Data preparation. Preprocessing continuous variables creating dummies. Homework with comments.html |
189B |
| 30. Data preparation. Preprocessing continuous variables creating dummies. Homework.html |
1.38KB |
| 31.1 Data preparation. Preprocessing the test dataset with comments.html |
189B |
| 31.2 Data preparation. Preprocessing the test dataset.html |
167B |
| 31. Data preparation. Preprocessing the test dataset.mp4 |
29.95MB |
| 31. Data preparation. Preprocessing the test dataset.srt |
5.51KB |
| 32.1 PD model data preparation.html |
156B |
| 32.2 PD model data preparation with comments.html |
178B |
| 32. PD model data preparation notebooks.html |
85B |
| 4.1 Calculating credit score.html |
165B |
| 4.1 LGD model estimating the accuracy of the model with comments.html |
202B |
| 4.1 Monitoring.html |
155B |
| 4.1 PD model estimation.html |
165B |
| 4.2 Calculating credit score with comments.html |
187B |
| 4.2 LGD model estimating the accuracy of the model.html |
180B |
| 4.2 Monitoring with comments.html |
177B |
| 4.2 PD model estimation with comments.html |
187B |
| 4. Calculating credit score.mp4 |
41.14MB |
| 4. Calculating credit score.srt |
7.54KB |
| 4. Completing 100%.html |
1.88KB |
| 4. Dependent variable Good Bad (default) definition.html |
141B |
| 4. Dependent variables and independent variables.html |
141B |
| 4. EAD model validation.html |
141B |
| 4. Evaluation of model performance accuracy and area under the curve (AUC).html |
141B |
| 4. Expected loss (EL) and its components PD, LGD and EAD.mp4 |
47.95MB |
| 4. Expected loss (EL) and its components PD, LGD and EAD.srt |
5.24KB |
| 4. Jupyter Dashboard - Part 1.mp4 |
11.57MB |
| 4. Jupyter Dashboard - Part 1.srt |
3.22KB |
| 4. LGD and EAD models dependent variables.html |
141B |
| 4. LGD model estimating the accuracy of the model.mp4 |
34.84MB |
| 4. LGD model estimating the accuracy of the model.srt |
5.95KB |
| 4. PD model estimation.mp4 |
24.92MB |
| 4. PD model estimation.srt |
4.93KB |
| 4. Population stability index calculation and interpretation.mp4 |
91.64MB |
| 4. Population stability index calculation and interpretation.srt |
14.26KB |
| 4. Preprocessing few continuous variables.html |
141B |
| 5.1 Build a logistic regression model with p-values.html |
165B |
| 5.1 Evaluation of model performance Gini and Kolmogorov-Smirnov with comments.html |
187B |
| 5.1 LGD and EAD models distribution of recovery rates and credit conversion factors with comments.html |
202B |
| 5.1 LGD model saving the model with comments.html |
202B |
| 5.1 Preprocessing few continuous variables Homework - Solution.html |
166B |
| 5.1 Shortcuts-for-Jupyter.pdf |
629.17KB |
| 5.2 Build a logistic regression model with p-values with comments.html |
187B |
| 5.2 Evaluation of model performance Gini and Kolmogorov-Smirnov.html |
165B |
| 5.2 LGD and EAD models distribution of recovery rates and credit conversion factors.html |
180B |
| 5.2 LGD model saving the model.html |
180B |
| 5.2 Preprocessing few continuous variables Homework - Solution with comments.html |
188B |
| 5. Build a logistic regression model with p-values.mp4 |
102.45MB |
| 5. Build a logistic regression model with p-values.srt |
14.49KB |
| 5. Calculating credit score.html |
141B |
| 5. Evaluation of model performance Gini and Kolmogorov-Smirnov.mp4 |
69.86MB |
| 5. Evaluation of model performance Gini and Kolmogorov-Smirnov.srt |
13.46KB |
| 5. Expected loss (EL) and its components PD, LGD and EAD.html |
141B |
| 5. Fine classing, weight of evidence, and coarse classing.mp4 |
55.34MB |
| 5. Fine classing, weight of evidence, and coarse classing.srt |
8.67KB |
| 5. Homework building an updated EAD model.html |
875B |
| 5. Jupyter Dashboard - Part 2.mp4 |
23.92MB |
| 5. Jupyter Dashboard - Part 2.srt |
6.64KB |
| 5. LGD and EAD models distribution of recovery rates and credit conversion factors.mp4 |
40.04MB |
| 5. LGD and EAD models distribution of recovery rates and credit conversion factors.srt |
7.71KB |
| 5. LGD model saving the model.mp4 |
23.83MB |
| 5. LGD model saving the model.srt |
4.02KB |
| 5. Population stability index calculation and interpretation.html |
141B |
| 5. Preprocessing few continuous variables Homework.html |
919B |
| 6.1 Dataset with new data (loan_data_2015.csv).html |
126B |
| 6.1 From credit score to PD.html |
165B |
| 6.1 LGD model stage 2 – linear regression.html |
180B |
| 6.1 Preprocessing few discrete variables with comments.html |
188B |
| 6.2 From credit score to PD with comments.html |
187B |
| 6.2 LGD model stage 2 – linear regression with comments.html |
202B |
| 6.2 Preprocessing few discrete variables.html |
166B |
| 6. Build a logistic regression model with p-values.html |
141B |
| 6. Capital adequacy, regulations, and the Basel II accord.mp4 |
51.03MB |
| 6. Capital adequacy, regulations, and the Basel II accord.srt |
5.79KB |
| 6. Evaluation of model performance Gini and Kolmogorov-Smirnov.html |
141B |
| 6. Fine classing, weight of evidence, and coarse classing.html |
141B |
| 6. From credit score to PD.mp4 |
23.20MB |
| 6. From credit score to PD.srt |
4.14KB |
| 6. Homework building an updated PD model.html |
820B |
| 6. Installing the sklearn package.mp4 |
9.65MB |
| 6. Installing the sklearn package.srt |
1.92KB |
| 6. LGD and EAD models distribution of recovery rates and credit conversion factors.html |
141B |
| 6. LGD model stage 2 – linear regression.mp4 |
36.06MB |
| 6. LGD model stage 2 – linear regression.srt |
5.26KB |
| 6. Preprocessing few discrete variables.mp4 |
46.30MB |
| 6. Preprocessing few discrete variables.srt |
8.93KB |
| 7. Capital adequacy, regulations, and the Basel II accord.html |
141B |
| 7. From credit score to PD.html |
141B |
| 7. Information value.mp4 |
44.70MB |
| 7. Information value.srt |
6.85KB |
| 7. Interpreting the coefficients in the PD model.mp4 |
35.23MB |
| 7. Interpreting the coefficients in the PD model.srt |
7.99KB |
| 7. LGD model stage 2 – linear regression with comments.html |
141B |
| 7. Preprocessing few discrete variables.html |
141B |
| 8.1 Check for missing values and clean.html |
166B |
| 8.1 LGD model stage 2 – linear regression evaluation.html |
180B |
| 8.1 Setting cut-offs.html |
165B |
| 8.2 Check for missing values and clean with comments.html |
188B |
| 8.2 LGD model stage 2 – linear regression evaluation with comments.html |
202B |
| 8.2 Setting cut-offs with comments.html |
187B |
| 8. Basel II approaches SA, F-IRB, and A-IRB.mp4 |
102.44MB |
| 8. Basel II approaches SA, F-IRB, and A-IRB.srt |
12.63KB |
| 8. Check for missing values and clean.mp4 |
25.08MB |
| 8. Check for missing values and clean.srt |
4.55KB |
| 8. Information value.html |
141B |
| 8. Interpreting the coefficients in the PD model.html |
141B |
| 8. LGD model stage 2 – linear regression evaluation.mp4 |
26.80MB |
| 8. LGD model stage 2 – linear regression evaluation.srt |
4.56KB |
| 8. Setting cut-offs.mp4 |
76.02MB |
| 8. Setting cut-offs.srt |
11.41KB |
| 9.1 Data preparation. Splitting data.html |
166B |
| 9.2 Data preparation. Splitting data with comments.html |
188B |
| 9. Basel II approaches SA, F-IRB, and A-IRB.html |
141B |
| 9. Check for missing values and clean.html |
141B |
| 9. Data preparation. Splitting data.mp4 |
59.38MB |
| 9. Data preparation. Splitting data.srt |
11.54KB |
| 9. LGD model stage 2 – linear regression evaluation.html |
141B |
| 9. Setting cut-offs.html |
141B |