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GetFreeCourses.Co-Udemy-Business Data Analytics & Intelligence with Python 2023

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种子名称: GetFreeCourses.Co-Udemy-Business Data Analytics & Intelligence with Python 2023
文件类型: 视频
文件数目: 240个文件
文件大小: 5.74 GB
收录时间: 2023-10-16 22:15
已经下载: 3
资源热度: 117
最近下载: 2024-5-18 20:36

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GetFreeCourses.Co-Udemy-Business Data Analytics & Intelligence with Python 2023.torrent
  • 1. Introduction/1. Python for Business Analytics & Intelligence.mp453.63MB
  • 1. Introduction/2. Introduction.mp47.27MB
  • 1. Introduction/3. Join Our Online Classroom!.mp475.33MB
  • 1. Introduction/5. Setting up the Course Material.mp457.96MB
  • 1. Introduction/6. The Modern Day Business Analyst.mp419.53MB
  • 10. Matching/1. Matching - Game Plan.mp48.12MB
  • 10. Matching/10. Python - Chi-square Test.mp431.14MB
  • 10. Matching/11. Python - Chi-square Loop.mp429.37MB
  • 10. Matching/12. Python - Other Variables.mp415.53MB
  • 10. Matching/13. The Curse of Dimensionality.mp47.46MB
  • 10. Matching/14. Python - Race Variable Transformation.mp466.81MB
  • 10. Matching/15. Python - Education Variables.mp440.82MB
  • 10. Matching/16. Python - Cleaning and Preparing Dataset.mp426.53MB
  • 10. Matching/17. Common Support Region.mp424.18MB
  • 10. Matching/18. Python - Logistic Regression and Debugging.mp473.92MB
  • 10. Matching/19. Python - Preparing for Common Support Region.mp436MB
  • 10. Matching/2. Matching.mp414.15MB
  • 10. Matching/20. Python - Common Support Region Visualization.mp410.93MB
  • 10. Matching/21. Python - Matching.mp439.11MB
  • 10. Matching/22. Robustness Checks.mp46.61MB
  • 10. Matching/23. Python - Robustness Check - Repeated experiments.mp453.74MB
  • 10. Matching/24. Python - Outcome Visualization.mp411.43MB
  • 10. Matching/25. Python - Robustness Check - Removing 1 Confounder.mp428.65MB
  • 10. Matching/26. CHALLENGE Introduction.mp434.33MB
  • 10. Matching/27. CHALLENGE Solutions.mp4107.51MB
  • 10. Matching/28. My Experience with Matching.mp47.75MB
  • 10. Matching/3. CASE STUDY Catholic Schools & Standardized Tests (Briefing).mp44.7MB
  • 10. Matching/4. Python - Directory and Libraries.mp418.14MB
  • 10. Matching/5. Python - Loading Data.mp425.91MB
  • 10. Matching/6. Unconfoundedness.mp48.48MB
  • 10. Matching/7. Python - Comparing Means.mp420MB
  • 10. Matching/8. Python - T-Test.mp427.3MB
  • 10. Matching/9. Python - T-Test Loop.mp430.27MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/1. RFM - Game Plan.mp42.28MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/10. Python - Monetary Variable.mp48.35MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/11. Python - Tidying up Dataframe.mp418.67MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/12. Python - Quartiles.mp441.83MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/13. Python - RFM Score.mp412.05MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/14. Python - RFM Function.mp422.44MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/15. Python - Applying RFM Function.mp415.71MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/16. Python - Results Summary.mp427.33MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/17. CHALLENGE Introduction.mp417.89MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/18. CHALLENGE Solutions.mp472.65MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/2. Value Based Segmentation.mp49.01MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/3. RFM Model.mp414.42MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/4. CASE STUDY Online Shopping (Briefing).mp42.92MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/5. Python - Directory and Libraries.mp414.26MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/6. Python - Loading Data.mp423.5MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/7. Python - Creating Sales Variable.mp416.06MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/8. Python - Date Variable.mp421.85MB
  • 12. RFM (Recency, Frequency, Monetary) Analysis/9. Python - Customer Level Aggregation.mp430.43MB
  • 13. Gaussian Mixture/1. Gaussian Mixture - Game Plan.mp42.69MB
  • 13. Gaussian Mixture/10. Python - Gaussian Mixture Model.mp48.58MB
  • 13. Gaussian Mixture/11. Python - Cluster Prediction and Assignment.mp414.33MB
  • 13. Gaussian Mixture/12. Python - Interpretation.mp478.69MB
  • 13. Gaussian Mixture/13. CHALLENGE Introduction.mp432.87MB
  • 13. Gaussian Mixture/14. CHALLENGE Solutions.mp4160.57MB
  • 13. Gaussian Mixture/15. My Experience with Segmentation.mp412.96MB
  • 13. Gaussian Mixture/2. Clustering.mp46.25MB
  • 13. Gaussian Mixture/3. Gaussian Mixture Model.mp413.84MB
  • 13. Gaussian Mixture/4. CASE STUDY Credit Cards #1 (Briefing).mp42.97MB
  • 13. Gaussian Mixture/5. Python - Directory and Data.mp414.66MB
  • 13. Gaussian Mixture/6. Python - Load Data.mp416.64MB
  • 13. Gaussian Mixture/7. Python - Transform Character variables.mp412.06MB
  • 13. Gaussian Mixture/8. AIC and BIC.mp410.14MB
  • 13. Gaussian Mixture/9. Python - Optimal Number of Clusters.mp438.75MB
  • 15. Random Forest/1. Random Forest - Game Plan.mp43.31MB
  • 15. Random Forest/10. Python - Isolate X and Y.mp413.08MB
  • 15. Random Forest/11. Python - Training and Test Set.mp431.62MB
  • 15. Random Forest/12. Python - Random Forest Model.mp417.84MB
  • 15. Random Forest/13. Python - Predictions.mp47.85MB
  • 15. Random Forest/14. Python - Classification Report and F1 score.mp424.7MB
  • 15. Random Forest/15. Python - Feature Importance.mp426.09MB
  • 15. Random Forest/16. Parameter Tuning.mp47.6MB
  • 15. Random Forest/17. Python - Parameter Grid.mp417.71MB
  • 15. Random Forest/18. Python - Parameter Tuning.mp448.13MB
  • 15. Random Forest/19. CHALLENGE Introduction.mp429.15MB
  • 15. Random Forest/2. Ensemble Learning and Random Forest.mp49.03MB
  • 15. Random Forest/20. CHALLENGE Solutions (Part 1).mp455.87MB
  • 15. Random Forest/21. CHALLENGE Solutions (Part 2).mp459.13MB
  • 15. Random Forest/3. How Decision Trees Work.mp417.27MB
  • 15. Random Forest/4. CASE STUDY Credit Cards #2 (Briefing).mp42.22MB
  • 15. Random Forest/5. Python - Directory and Libraries.mp413.94MB
  • 15. Random Forest/6. Python - Loading Data.mp419.72MB
  • 15. Random Forest/7. Python - Transform Object into Numerical Variables.mp413.53MB
  • 15. Random Forest/8. Python - Summary Statistics.mp423.58MB
  • 15. Random Forest/9. Random Forest Quirks.mp46.68MB
  • 16. Facebook Prophet/1. Facebook Prophet - Game Plan.mp43.39MB
  • 16. Facebook Prophet/10. Python - Easter Holidays.mp428.46MB
  • 16. Facebook Prophet/11. Python - Black Friday.mp418.53MB
  • 16. Facebook Prophet/12. Python - Combining Events and Preparing Dataframe.mp417.02MB
  • 16. Facebook Prophet/13. Training and Test Set.mp46.36MB
  • 16. Facebook Prophet/14. Python - Training and Test Set.mp412.71MB
  • 16. Facebook Prophet/15. Facebook Prophet Parameters.mp48.07MB
  • 16. Facebook Prophet/16. Additive vs. Multiplicative Seasonality.mp410.06MB
  • 16. Facebook Prophet/17. Facebook Prophet Model.mp439.62MB
  • 16. Facebook Prophet/18. Python - Regressor Coefficients.mp410.52MB
  • 16. Facebook Prophet/19. Python - Future Dataframe.mp434.63MB
  • 16. Facebook Prophet/2. Structural Time Series.mp48.24MB
  • 16. Facebook Prophet/20. Python - Forecasting.mp418.63MB
  • 16. Facebook Prophet/21. Python - Accuracy Assessment.mp422.59MB
  • 16. Facebook Prophet/22. Python - Visualization.mp439.24MB
  • 16. Facebook Prophet/23. Cross-validation.mp42.9MB
  • 16. Facebook Prophet/24. Python - Cross-validation.mp459.86MB
  • 16. Facebook Prophet/25. Parameters to tune.mp43.84MB
  • 16. Facebook Prophet/26. Python - Parameter Grid.mp425.54MB
  • 16. Facebook Prophet/27. Python - Parameter Tuning.mp456.49MB
  • 16. Facebook Prophet/28. CHALLENGE Introduction.mp424.46MB
  • 16. Facebook Prophet/29. CHALLENGE Solutions (Part 1).mp452.18MB
  • 16. Facebook Prophet/3. Facebook Prophet.mp411.83MB
  • 16. Facebook Prophet/30. CHALLENGE Solutions (Part 2).mp477.81MB
  • 16. Facebook Prophet/31. CHALLENGE Solutions (Part 3).mp448.96MB
  • 16. Facebook Prophet/32. Forecasting at Uber.mp415.61MB
  • 16. Facebook Prophet/4. CASE STUDY Wikipedia (Briefing).mp42.63MB
  • 16. Facebook Prophet/5. Python - Directory and Libraries.mp414.28MB
  • 16. Facebook Prophet/6. Python - Loading Data.mp414.44MB
  • 16. Facebook Prophet/7. Python - Transforming Date Variable.mp420.68MB
  • 16. Facebook Prophet/8. Python - Renaming Variables.mp410.17MB
  • 16. Facebook Prophet/9. Dynamic Holidays.mp46.44MB
  • 17. Where To Go From Here/1. Thank You!.mp416.86MB
  • 3. Basic Statistics/1. Basic Statistics - Game Plan.mp42.91MB
  • 3. Basic Statistics/10. Python - Mode.mp418.82MB
  • 3. Basic Statistics/11. EXERCISE Python - Mode.mp412.62MB
  • 3. Basic Statistics/12. Correlation.mp429.39MB
  • 3. Basic Statistics/13. Python - Correlation.mp454.04MB
  • 3. Basic Statistics/14. EXERCISE Python - Correlation.mp424.16MB
  • 3. Basic Statistics/15. Standard Deviation.mp47.26MB
  • 3. Basic Statistics/16. Python - Standard Deviation.mp417.66MB
  • 3. Basic Statistics/17. EXERCISE Python - Standard Deviation.mp46.48MB
  • 3. Basic Statistics/18. CASE STUDY Moneyball.mp412.45MB
  • 3. Basic Statistics/2. Arithmetic Mean.mp49.12MB
  • 3. Basic Statistics/3. CASE STUDY Moneyball (Briefing).mp42.19MB
  • 3. Basic Statistics/4. Python - Directory, Libraries and Data.mp451.3MB
  • 3. Basic Statistics/5. Python - Mean.mp459.67MB
  • 3. Basic Statistics/6. EXERCISE Python - Mean.mp416.48MB
  • 3. Basic Statistics/7. Median and Mode.mp48.43MB
  • 3. Basic Statistics/8. Python - Median.mp425.38MB
  • 3. Basic Statistics/9. EXERCISE Python - Median.mp420.28MB
  • 4. Intermediary Statistics/1. Intermediary Statistics - Game Plan.mp41.82MB
  • 4. Intermediary Statistics/10. EXERCISE Python - Shapiro-Wilks.mp415.07MB
  • 4. Intermediary Statistics/11. Standard Error of the Mean.mp48.15MB
  • 4. Intermediary Statistics/12. Python - Standard Error.mp428.84MB
  • 4. Intermediary Statistics/13. EXERCISE Python - Standard Error.mp412.57MB
  • 4. Intermediary Statistics/14. Z-Score.mp48.45MB
  • 4. Intermediary Statistics/15. Confidence interval.mp442.96MB
  • 4. Intermediary Statistics/16. Python - Confidence Interval.mp445.81MB
  • 4. Intermediary Statistics/17. EXERCISE Python - Confidence Interval.mp416.16MB
  • 4. Intermediary Statistics/18. T-test.mp46.6MB
  • 4. Intermediary Statistics/19. CASE STUDY Remote Work Predictions (Briefing).mp42.45MB
  • 4. Intermediary Statistics/2. Normal Distribution.mp412.81MB
  • 4. Intermediary Statistics/20. Python - T-test.mp465.47MB
  • 4. Intermediary Statistics/21. EXERCISE Python - T-test.mp431.94MB
  • 4. Intermediary Statistics/22. Chi-square test.mp48.78MB
  • 4. Intermediary Statistics/23. Python - Chi-square test.mp450.5MB
  • 4. Intermediary Statistics/24. EXERCISE Python - Chi-square.mp422.71MB
  • 4. Intermediary Statistics/25. Powerposing and p-hacking.mp415.74MB
  • 4. Intermediary Statistics/3. CASE STUDY Wine Quality (Briefing).mp49.8MB
  • 4. Intermediary Statistics/4. Python - Preparing Script and Loading Data.mp428.58MB
  • 4. Intermediary Statistics/5. Python - Normal Distribution Visualization.mp440.87MB
  • 4. Intermediary Statistics/6. EXERCISE Python - Normal Distribution.mp428.28MB
  • 4. Intermediary Statistics/7. P-value.mp427.3MB
  • 4. Intermediary Statistics/8. Shapiro-Wilks Test.mp46.11MB
  • 4. Intermediary Statistics/9. Python - Shapiro-Wilks Test.mp451.1MB
  • 5. Linear Regression/1. Linear Regression - Game Plan.mp43.58MB
  • 5. Linear Regression/10. Dummy Variable Trap.mp412.13MB
  • 5. Linear Regression/11. Python - Dummy Variable.mp417.85MB
  • 5. Linear Regression/12. EXERCISE Python - Linear Regression.mp436.01MB
  • 5. Linear Regression/2. CASE STUDY Diamonds (Briefing).mp43.34MB
  • 5. Linear Regression/3. Linear Regression.mp416.24MB
  • 5. Linear Regression/4. Python - Preparing Script and Loading Data.mp427.47MB
  • 5. Linear Regression/5. Python - Isolate X and Y.mp411.04MB
  • 5. Linear Regression/6. Python - Adding Constant.mp411.47MB
  • 5. Linear Regression/7. Linear Regression Output.mp433.44MB
  • 5. Linear Regression/8. Python - Linear Regression model and summary.mp421.95MB
  • 5. Linear Regression/9. Python - Plotting Regression.mp426.09MB
  • 6. Multilinear Regression/1. Multilinear Regression - Game Plan.mp44.19MB
  • 6. Multilinear Regression/10. Python - For Loop.mp428.25MB
  • 6. Multilinear Regression/11. Python - Creating Dummy Variables.mp417.55MB
  • 6. Multilinear Regression/12. Python - Isolate X and Y.mp420.71MB
  • 6. Multilinear Regression/13. Python - Adding Constant.mp47.02MB
  • 6. Multilinear Regression/14. Under and Over Fitting.mp45.09MB
  • 6. Multilinear Regression/15. Training and Test Set.mp42.8MB
  • 6. Multilinear Regression/16. Python - Train and Test Split.mp413.93MB
  • 6. Multilinear Regression/17. Python - Multilinear Regression.mp442.77MB
  • 6. Multilinear Regression/18. Accuracy KPIs (Key Performance Indicators).mp414.54MB
  • 6. Multilinear Regression/19. Python - Model Predictions.mp49.76MB
  • 6. Multilinear Regression/2. The Concept of Multilinear Regression.mp45.31MB
  • 6. Multilinear Regression/20. Python - Accuracy Assessment.mp437.55MB
  • 6. Multilinear Regression/21. CHALLENGE Introduction.mp427.71MB
  • 6. Multilinear Regression/22. CHALLENGE Solutions.mp4110.61MB
  • 6. Multilinear Regression/3. CASE STUDY Professors' Salary (Briefing).mp43.09MB
  • 6. Multilinear Regression/4. Python - Preparing Script and Loading Data.mp432.85MB
  • 6. Multilinear Regression/5. Python - Summary Statistics.mp418.82MB
  • 6. Multilinear Regression/6. Outliers.mp48.82MB
  • 6. Multilinear Regression/7. Python - Plotting Continuous Variables.mp439.35MB
  • 6. Multilinear Regression/8. Python - Correlation Matrix.mp421.07MB
  • 6. Multilinear Regression/9. Python - Categorical Variables.mp426.51MB
  • 7. Logistic Regression/1. Logistic Regression - Game Plan.mp43.15MB
  • 7. Logistic Regression/10. Python - Training and Test Set.mp421.64MB
  • 7. Logistic Regression/11. How to Read Logistic Regression Coefficients.mp410.89MB
  • 7. Logistic Regression/12. Python - Logistic Regression.mp418.6MB
  • 7. Logistic Regression/13. Python - Function to Read Coefficients.mp456.71MB
  • 7. Logistic Regression/14. Python - Predictions.mp421.27MB
  • 7. Logistic Regression/15. Confusion Matrix.mp424.52MB
  • 7. Logistic Regression/16. Python - Confusion Matrix.mp429.64MB
  • 7. Logistic Regression/17. Python - Manual Accuracy Assessment.mp438.42MB
  • 7. Logistic Regression/18. Python - Classification Report.mp419.59MB
  • 7. Logistic Regression/19. CHALLENGE Introduction.mp429.26MB
  • 7. Logistic Regression/2. CASE STUDY Spam Emails (Briefing).mp42.97MB
  • 7. Logistic Regression/20. CHALLENGE Solutions.mp490.65MB
  • 7. Logistic Regression/3. Logistic Regression.mp410.13MB
  • 7. Logistic Regression/4. Python - Preparing Script and Loading Data.mp427.8MB
  • 7. Logistic Regression/5. Python - Summary Statistics.mp427.94MB
  • 7. Logistic Regression/6. Python - Histogram and Outlier Removal.mp448.25MB
  • 7. Logistic Regression/7. Python - Correlation Matrix.mp415.09MB
  • 7. Logistic Regression/8. Python - Transforming Dependent Variable.mp417.33MB
  • 7. Logistic Regression/9. Python - Prepare X and Y.mp411.55MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/1. Why Econometrics and Causal Inference.mp418.35MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/10. Assumptions.mp412.37MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/11. Python - Load Control Groups.mp429.03MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/12. Python - Preparing DataFrame.mp454.04MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/13. Python - Preparing for Correlation Matrix.mp419.74MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/14. Correlation Recap and Stationarity.mp416.2MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/15. Python - Stationarity.mp453.83MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/16. Python - Correlation.mp430.15MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/17. Python - Google Causal Impact Setup.mp415.98MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/18. Python - Google Causal Impact.mp439.9MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/19. Interpretation of Results.mp426.46MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/2. Google Causal Impact - Game Plan.mp43.58MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/20. Python - Impact Results.mp444.53MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/21. CHALLENGE Introduction.mp440.07MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/22. CHALLENGE Solutions.mp4103.51MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/23. EXERCISE Imposter Syndrome.mp439.22MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/3. Time Series Data.mp45.72MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/4. CASE STUDY Bitcoin Pricing (Briefing).mp414.2MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/5. Difference-in-Differences Framework.mp48.37MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/6. Causal Impact Step-by-Step.mp45.81MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/7. Python - Installing and Importing Libraries.mp418.78MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/8. Python - Defining Dates.mp418.38MB
  • 9. Google Causal Impact (Econometrics and Causal Inference)/9. Python - Bitcoin Price loading.mp433.59MB