Course Curriculum
| Welcome | |||
| Learning Objectives | 00:00:00 | ||
| Why Exploration and Visualization | |||
| Introduction | 00:03:00 | ||
| Data beats algorithm | 00:05:00 | ||
| Why Data Analysis | 00:05:00 | ||
| How Much Data? | 00:06:00 | ||
| Sampling data | 00:05:00 | ||
| Data Quality & Variety | 00:08:00 | ||
| Feature Engineering | 00:10:00 | ||
| Exploration and Visualization using R | |||
| Introduction | 00:07:00 | ||
| Basic Commands and Parameters | 00:04:00 | ||
| Core R Graphics | |||
| The Iris Dataset | 00:02:00 | ||
| Box Plots | 00:03:00 | ||
| Grammer of Graphics | 00:08:00 | ||
| Visualizing relations | 00:12:00 | ||
| Creating exploratory plots | 00:25:00 | ||
| Lattice Graphics | |||
| Introduction | 00:06:00 | ||
| Examples | 00:33:00 | ||
| GGPlot2 Graphics | |||
| Introduction | 00:06:00 | ||
| Grammer | 00:06:00 | ||
| Visual aesthetics | 00:08:00 | ||
| Modifying aesthetics | 00:11:00 | ||
| Objects & layers | 00:10:00 | ||
| Data Exploration and Feature Engineering using R | 01:30:00 | ||
| Storytelling with the Titanic | |||
| Seperating segments | 00:12:00 | ||
| Data exploration | 00:04:00 | ||
| Exploratory Data Analysis Part 1 | 00:11:00 | ||
| Exploratory Data Analysis Part 2 | 00:07:00 | ||
| Data wrangling | 00:12:00 | ||
| Pie charts | 00:13:00 | ||
| Box plots | 00:14:00 | ||
| Data Exploration Quiz | |||
| Data Exploration Quiz | 00:10:00 | ||
| Data Exploration Deliberate Practice | |||
| Data Exploration Deliberate Practice | 01:30:00 | ||
| Supplemental Exercise | |||
| Data Exploration and Visualization with Python | 01:30:00 | ||
| Data Exploration and Feature Engineering with Adult dataset (Python) | 01:30:00 | ||
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