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