1. Introduction
2. Sandbox Setup
3. Data Science Methodology
4. Step 1 - Describe Use Case
5. Step 2 - Describe Data
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Describe Data - Concepts (7:49)
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Describe Data - Tasks and Deliverables (7:07)
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Step 2 - Task 1. Describe Data Sources (12:11)
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Step 2 - Task 2. Explore Data Set (3:49)
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Step 2 - Task 3. Classify Data Set (2:00)
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Step 2 - Task 4. Collect Basic Statistics (2:15)
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Step 2 - Task 5. Verify Data Quality (4:50)
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Quizzes
6. Step 3 - Prepare Data
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Data Preparation & Feature Engineering Overview (13:49)
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Step 3 - Task 1. Select Datasets (6:36)
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Step 3 - Task 2. Filter Datasets (3:11)
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Step 3 - Task 3. Reformat Datasets (7:25)
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Step 3 - Task 4. Transform Datasets (10:27)
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Step 3 - Task 5. Sort Datasets (7:37)
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Step 3 - Task 6. Feature Engineering (11:46)
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Step 3 - Task 7. Merge Datasets (14:09)
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Quizzes
7. Step 4 - Develop Model
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Develop Model Overview (3:26)
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Step 4 - Task 1. Prediction Set-up (22:05)
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Step 4 - Task 2. Time Series Forecasting (13:51)
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Step 4 - Task 3. Regression Models (24:56)
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Step 4 - Task 4. Classification (19:58)
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Step 4 - Task 5. Classification using Clustering (16:47)
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Step 4 - Task 6. Connecting the dots (26:45)
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Step 4 - Task 7. Graph Analytics (13:56)
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Quizzes
8. Step 5 - Evaluate Model
9. Step 6 - Deploy Model
10. Step 7 - Optimize Model
11. Summary
