Этот материал находится в платной подписке. Оформи премиум подписку и смотри или слушай Python for Business Data Analytics & Intelligence, а также все другие курсы, прямо сейчас!
Премиум
  • Урок 1. 00:02:35
    Python for Business Analytics & Intelligence
  • Урок 2. 00:01:56
    Introduction
  • Урок 3. 00:07:08
    Setting up the Course Material
  • Урок 4. 00:05:01
    The Modern Day Business Analyst
  • Урок 5. 00:01:07
    Basic Statistics - Game Plan
  • Урок 6. 00:01:57
    Arithmetic Mean
  • Урок 7. 00:00:59
    CASE STUDY: Moneyball (Briefing)
  • Урок 8. 00:08:04
    Python - Directory, Libraries and Data
  • Урок 9. 00:09:17
    Python - Mean
  • Урок 10. 00:02:21
    EXERCISE: Python - Mean
  • Урок 11. 00:02:42
    Median and Mode
  • Урок 12. 00:05:02
    Python - Median
  • Урок 13. 00:02:58
    EXERCISE: Python - Median
  • Урок 14. 00:03:04
    Python - Mode
  • Урок 15. 00:01:37
    EXERCISE: Python - Mode
  • Урок 16. 00:04:17
    Correlation
  • Урок 17. 00:08:42
    Python - Correlation
  • Урок 18. 00:03:34
    EXERCISE: Python - Correlation
  • Урок 19. 00:02:08
    Standard Deviation
  • Урок 20. 00:02:24
    Python - Standard Deviation
  • Урок 21. 00:01:05
    EXERCISE: Python - Standard Deviation
  • Урок 22. 00:03:57
    CASE STUDY: Moneyball
  • Урок 23. 00:00:47
    Intermediary Statistics - Game Plan
  • Урок 24. 00:03:01
    Normal Distribution
  • Урок 25. 00:02:23
    CASE STUDY: Wine Quality (Briefing)
  • Урок 26. 00:05:01
    Python - Preparing Script and Loading Data
  • Урок 27. 00:09:29
    Python - Normal Distribution Visualization
  • Урок 28. 00:05:42
    EXERCISE: Python - Normal Distribution
  • Урок 29. 00:05:34
    P-Value
  • Урок 30. 00:01:52
    Shapiro-Wilks Test
  • Урок 31. 00:07:43
    Python - Shapiro-Wilks Test
  • Урок 32. 00:02:50
    EXERCISE: Python - Shapiro-Wilks
  • Урок 33. 00:02:37
    Standard Error of the Mean
  • Урок 34. 00:04:25
    Python - Standard Error
  • Урок 35. 00:02:11
    EXERCISE: Python - Standard Error
  • Урок 36. 00:02:41
    Z-Score
  • Урок 37. 00:05:49
    Confidence Interval
  • Урок 38. 00:06:24
    Python - Confidence Interval
  • Урок 39. 00:02:20
    EXERCISE: Python - Confidence Interval
  • Урок 40. 00:02:18
    T-test
  • Урок 41. 00:00:40
    CASE STUDY: Remote Work Predictions (Briefing)
  • Урок 42. 00:10:21
    Python - T-test
  • Урок 43. 00:05:23
    EXERCISE: Python - T-test
  • Урок 44. 00:02:29
    Chi-square test
  • Урок 45. 00:07:30
    Python - Chi-square test
  • Урок 46. 00:03:15
    EXERCISE: Python - Chi-square
  • Урок 47. 00:03:21
    Powerposing and p-hacking
  • Урок 48. 00:01:28
    Linear Regression - Game Plan
  • Урок 49. 00:00:58
    CASE STUDY: Diamonds (Briefing)
  • Урок 50. 00:05:12
    Linear Regression
  • Урок 51. 00:04:37
    Python - Preparing Script and Loading Data
  • Урок 52. 00:01:48
    Python - Isolate X and Y
  • Урок 53. 00:02:44
    Python - Adding Constant
  • Урок 54. 00:03:37
    Linear Regression Output
  • Урок 55. 00:03:21
    Python - Linear Regression Model and Summary
  • Урок 56. 00:04:24
    Python - Plotting Regression
  • Урок 57. 00:03:10
    Dummy Variable Trap
  • Урок 58. 00:03:36
    Python - Dummy Variable
  • Урок 59. 00:05:52
    EXERCISE: Python - Linear Regression
  • Урок 60. 00:01:35
    Multilinear Regression - Game Plan
  • Урок 61. 00:01:46
    The Concept of Multilinear Regression
  • Урок 62. 00:00:46
    CASE STUDY: Professors' Salary (Briefing)
  • Урок 63. 00:05:06
    Python - Preparing Script and Loading Data
  • Урок 64. 00:03:00
    Python - Summary Statistics
  • Урок 65. 00:02:44
    Outliers
  • Урок 66. 00:04:55
    Python - Plotting Continuous Variables
  • Урок 67. 00:02:52
    Python - Correlation Matrix
  • Урок 68. 00:04:31
    Python - Categorical Variables
  • Урок 69. 00:04:44
    Python - For Loop
  • Урок 70. 00:03:10
    Python - Creating Dummy Variables
  • Урок 71. 00:03:29
    Python - Isolate X and Y
  • Урок 72. 00:01:27
    Python - Adding Constant
  • Урок 73. 00:01:33
    Under and Over Fitting
  • Урок 74. 00:01:04
    Training and Test Set
  • Урок 75. 00:02:43
    Python - Train and Test Split
  • Урок 76. 00:05:02
    Python - Multilinear Regression
  • Урок 77. 00:03:20
    Accuracy KPIs (Key Performance Indicators)
  • Урок 78. 00:01:32
    Python - Model Predictions
  • Урок 79. 00:05:37
    Python - Accuracy Assessment
  • Урок 80. 00:05:09
    CHALLENGE: Introduction
  • Урок 81. 00:16:00
    CHALLENGE: Solutions
  • Урок 82. 00:01:14
    Logistic Regression - Game Plan
  • Урок 83. 00:01:01
    CASE STUDY: Spam Emails (Briefing)
  • Урок 84. 00:02:07
    Logistic Regression
  • Урок 85. 00:04:17
    Python - Preparing Script and Loading Data
  • Урок 86. 00:03:20
    Python - Summary Statistics
  • Урок 87. 00:07:03
    Python - Histogram and Outlier Removal
  • Урок 88. 00:02:33
    Python - Correlation Matrix
  • Урок 89. 00:02:40
    Python - Transforming Dependent Variable
  • Урок 90. 00:02:10
    Python - Prepare X and Y
  • Урок 91. 00:02:43
    Python - Training and Test Set
  • Урок 92. 00:02:41
    How to Read Logistic Regression Coefficients
  • Урок 93. 00:02:20
    Python - Logistic Regression
  • Урок 94. 00:08:31
    Python - Function to Read Coefficients
  • Урок 95. 00:03:07
    Python - Predictions
  • Урок 96. 00:06:18
    Confusion Matrix
  • Урок 97. 00:05:26
    Python - Confusion Matrix
  • Урок 98. 00:07:06
    Python - Manual Accuracy Assessment
  • Урок 99. 00:02:46
    Python - Classification Report
  • Урок 100. 00:04:50
    CHALLENGE: Introduction
  • Урок 101. 00:13:40
    CHALLENGE: Solutions
  • Урок 102. 00:04:21
    Why Econometrics and Causal Inference
  • Урок 103. 00:01:21
    Google Causal Impact - Game Plan
  • Урок 104. 00:01:31
    Time Series Data
  • Урок 105. 00:02:29
    CASE STUDY: Bitcoin Pricing (Briefing)
  • Урок 106. 00:02:22
    Difference-in-Differences Framework
  • Урок 107. 00:02:21
    Causal Impact Step-by-Step
  • Урок 108. 00:03:55
    Python - Installing and Importing Libraries
  • Урок 109. 00:03:35
    Python - Defining Dates
  • Урок 110. 00:05:13
    Python - Bitcoin Price loading
  • Урок 111. 00:02:55
    Assumptions
  • Урок 112. 00:04:00
    Python - Load Control Groups
  • Урок 113. 00:06:01
    Python - Preparing DataFrame
  • Урок 114. 00:02:43
    Python - Preparing for Correlation Matrix
  • Урок 115. 00:04:17
    Correlation Recap and Stationarity
  • Урок 116. 00:07:07
    Python - Stationarity
  • Урок 117. 00:03:23
    Python - Correlation
  • Урок 118. 00:02:42
    Python - Google Causal Impact Setup
  • Урок 119. 00:03:24
    Python - Google Causal Impact
  • Урок 120. 00:04:18
    Interpretation of Results
  • Урок 121. 00:05:05
    Python - Impact Results
  • Урок 122. 00:07:15
    CHALLENGE: Introduction
  • Урок 123. 00:13:14
    CHALLENGE: Solutions
  • Урок 124. 00:02:51
    Matching - Game Plan
  • Урок 125. 00:02:52
    Matching
  • Урок 126. 00:01:01
    CASE STUDY: Catholic Schools & Standardized Tests (Briefing)
  • Урок 127. 00:02:54
    Python - Directory and Libraries
  • Урок 128. 00:02:25
    Python - Loading Data
  • Урок 129. 00:02:17
    Unconfoundedness
  • Урок 130. 00:02:43
    Python - Comparing Means
  • Урок 131. 00:04:10
    Python - T-Test
  • Урок 132. 00:04:39
    Python - T-Test Loop
  • Урок 133. 00:03:28
    Python - Chi-square Test
  • Урок 134. 00:04:27
    Python - Chi-square Loop
  • Урок 135. 00:01:50
    Python - Other Variables
  • Урок 136. 00:01:41
    The Curse of Dimensionality
  • Урок 137. 00:07:00
    Python - Race Variable Transformation
  • Урок 138. 00:05:31
    Python - Education Variables
  • Урок 139. 00:03:32
    Python - Cleaning and Preparing Dataset
  • Урок 140. 00:04:05
    Common Support Region
  • Урок 141. 00:07:23
    Python - Logistic Regression and Debugging
  • Урок 142. 00:05:40
    Python - Preparing for Common Support Region
  • Урок 143. 00:01:42
    Python - Common Support Region Visualization
  • Урок 144. 00:04:52
    Python - Matching
  • Урок 145. 00:02:14
    Robustness Checks
  • Урок 146. 00:07:01
    Python - Robustness Check - Repeated experiments
  • Урок 147. 00:01:56
    Python - Outcome Visualization
  • Урок 148. 00:03:39
    Python - Robustness Check - Removing 1 confounder
  • Урок 149. 00:05:26
    CHALLENGE: Introduction
  • Урок 150. 00:14:04
    CHALLENGE: Solutions
  • Урок 151. 00:02:42
    My Experience with Matching
  • Урок 152. 00:00:46
    RFM - Game Plan
  • Урок 153. 00:02:53
    Value Based Segmentation
  • Урок 154. 00:04:54
    RFM Model
  • Урок 155. 00:00:54
    CASE STUDY: Online Shopping (Briefing)
  • Урок 156. 00:02:18
    Python - Directory and Libraries
  • Урок 157. 00:02:30
    Python - Loading Data
  • Урок 158. 00:01:46
    Python - Creating Sales Variable
  • Урок 159. 00:03:34
    Python - Date Variable
  • Урок 160. 00:03:50
    Python - Customer Level Aggregation
  • Урок 161. 00:01:24
    Python - Monetary Variable
  • Урок 162. 00:02:53
    Python - Tidying up Dataframe
  • Урок 163. 00:06:35
    Python - Quartiles
  • Урок 164. 00:01:52
    Python - RFM Score
  • Урок 165. 00:04:42
    Python - RFM Function
  • Урок 166. 00:02:10
    Python - Applying RFM Function
  • Урок 167. 00:04:30
    Python - Results Summary
  • Урок 168. 00:03:32
    CHALLENGE: Introduction
  • Урок 169. 00:12:17
    CHALLENGE: Solutions
  • Урок 170. 00:01:11
    Gaussian Mixture - Game Plan
  • Урок 171. 00:02:10
    Clustering
  • Урок 172. 00:03:58
    Gaussian Mixture Model
  • Урок 173. 00:00:54
    CASE STUDY: Credit Cards #1 (Briefing)
  • Урок 174. 00:02:12
    Python - Directory and Data
  • Урок 175. 00:01:51
    Python - Load Data
  • Урок 176. 00:01:22
    Python - Transform Character variables
  • Урок 177. 00:02:16
    AIC and BIC
  • Урок 178. 00:06:25
    Python - Optimal Number of Clusters
  • Урок 179. 00:01:12
    Python - Gaussian Mixture Model
  • Урок 180. 00:02:51
    Python - Cluster Prediction and Assignment
  • Урок 181. 00:07:47
    Python - Interpretation
  • Урок 182. 00:04:36
    CHALLENGE: Introduction
  • Урок 183. 00:18:05
    CHALLENGE: Solutions
  • Урок 184. 00:03:16
    My Experience with Segmentation
  • Урок 185. 00:01:06
    Random Forest - Game Plan
  • Урок 186. 00:02:17
    Ensemble Learning and Random Forest
  • Урок 187. 00:04:20
    How Decision Trees Work
  • Урок 188. 00:00:38
    CASE STUDY: Credit Cards #2 (Briefing)
  • Урок 189. 00:02:03
    Python - Directory and Libraries
  • Урок 190. 00:01:51
    Python - Loading Data
  • Урок 191. 00:01:44
    Python - Transform Object into Numerical Variables
  • Урок 192. 00:02:22
    Python - Summary Statistics
  • Урок 193. 00:02:31
    Random Forest Quirks
  • Урок 194. 00:01:33
    Python - Isolate X and Y
  • Урок 195. 00:03:41
    Python - Training and Test Set
  • Урок 196. 00:03:00
    Python - Random Forest Model
  • Урок 197. 00:01:19
    Python - Predictions
  • Урок 198. 00:03:45
    Python - Classification Report and F1 score
  • Урок 199. 00:04:23
    Python - Feature Importance
  • Урок 200. 00:02:46
    Parameter Tuning
  • Урок 201. 00:03:15
    Python - Parameter Grid
  • Урок 202. 00:07:11
    Python - Parameter Tuning
  • Урок 203. 00:04:25
    CHALLENGE: Introduction
  • Урок 204. 00:08:30
    CHALLENGE: Solutions (Part 1)
  • Урок 205. 00:09:41
    CHALLENGE: Solutions (Part 2)
  • Урок 206. 00:01:21
    Facebook Prophet - Game Plan
  • Урок 207. 00:02:26
    Structural Time Series
  • Урок 208. 00:03:38
    Facebook Prophet
  • Урок 209. 00:00:52
    CASE STUDY: Wikipedia (Briefing)
  • Урок 210. 00:02:06
    Python - Directory and Libraries
  • Урок 211. 00:02:35
    Python - Loading Data
  • Урок 212. 00:02:49
    Python - Transforming Date Variable
  • Урок 213. 00:01:32
    Python - Renaming Variables
  • Урок 214. 00:02:11
    Dynamic Holidays
  • Урок 215. 00:05:17
    Python - Easter Holidays
  • Урок 216. 00:02:51
    Python - Black Friday
  • Урок 217. 00:02:34
    Python - Combining Events and Preparing Dataframe
  • Урок 218. 00:02:13
    Training and Test Set
  • Урок 219. 00:03:18
    Python - Training and Test Set
  • Урок 220. 00:02:14
    Facebook Prophet Parameters
  • Урок 221. 00:02:38
    Additive vs. Multiplicative Seasonality
  • Урок 222. 00:04:46
    Facebook Prophet Model
  • Урок 223. 00:01:50
    Python - Regressor Coefficients
  • Урок 224. 00:04:38
    Python - Future Dataframe
  • Урок 225. 00:02:20
    Python - Forecasting
  • Урок 226. 00:03:42
    Python - Accuracy Assessment
  • Урок 227. 00:05:41
    Python - Visualization
  • Урок 228. 00:01:08
    Cross-validation
  • Урок 229. 00:08:00
    Python - Cross-validation
  • Урок 230. 00:01:23
    Parameters to tune
  • Урок 231. 00:04:04
    Python - Parameter Grid
  • Урок 232. 00:07:29
    Python - Parameter Tuning
  • Урок 233. 00:04:48
    CHALLENGE: Introduction
  • Урок 234. 00:09:18
    CHALLENGE: Solutions (Part 1)
  • Урок 235. 00:11:08
    CHALLENGE: Solutions (Part 2)
  • Урок 236. 00:08:09
    CHALLENGE: Solutions (Part 3)
  • Урок 237. 00:04:39
    Forecasting at Uber
  • Урок 238. 00:01:18
    Thank You!