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CodeSignal

Intro to Data Cleaning and Preprocessing with Titanic

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Overview

This comprehensive course specializes in data cleaning and preprocessing techniques in Python, preparing you to apply these techniques in predictive modeling. The course covers a range of relevant topics, from missing data handling to feature engineering.

Syllabus

  • Unit 1: Data Cleaning Techniques: Detecting and Handling Missing Data
    • Detecting and Handling Missing Data in the Titanic Dataset
    • Replacing Mean Imputation with Median Imputation
    • Fixing Missing Data Handling in Titanic Dataset
    • Detecting and Filling Missing Values in the Titanic Dataset
    • Handling and Visualizing Missing Data in Titanic Dataset
  • Unit 2: Data Cleaning Techniques: Working with Categorical Data Encoding and Transformation
    • Exploring Encoding of Categorical Data in the Titanic Dataset
    • Exploring Different Columns with Categorical Data Encoding in Titanic Dataset
    • Fixing Conditional Encoding Issue in the Titanic Dataset
    • Encoding Categorical Data in the Titanic Dataset
    • Mastering Encoding Techniques with the Titanic Data Set
  • Unit 3: Diving into Data Transformation and Scaling Techniques
    • Applying Scaling Techniques to Titanic Dataset
    • Applying Robust Scaling to 'fare' Column
    • Applying Robust Scaling on the Titanic Dataset
    • Applying Min-Max and Robust Scaling to Titanic Dataset
    • Applying Standard, Min-Max, and Robust Scaling Techniques to Titanic Dataset by Hand
  • Unit 4: Navigating through Outliers: Detection and Handling Techniques
    • Detecting and Handling Outliers in Titanic Dataset
    • Detecting and Handling Fare Outliers in the Titanic Dataset
    • Adjusting Fare Anomalies in the Titanic Dataset
    • Detecting Fare Outliers Using the Z-score Method in Titanic Dataset
    • Navigating the Ocean of Outliers in Age Data for Titanic Dataset
  • Unit 5: Understanding and Handling Redundant or Correlated Features in Datasets
    • Visualizing and Handling Redundant Features in the Titanic Dataset
    • Analyzing Correlations in Titanic Data Excluding the Survival Rate
    • Unraveling the Galactic Web of Correlation with a Heatmap
    • Visualizing and Handling Correlated Features in the Titanic Dataset
    • Visualizing and Cleaning Redundant Features from Titanic Dataset
  • Unit 6: Engineering New Features for Better Predictions
    • Investigating Family Sizes and Solitude on the Titanic
    • Changing Age Group Categories in Titanic Dataset
    • Debug and Perfect Titanic Dataset Feature Engineering
    • Adding New Features and Age Groups in Titanic Dataset
    • Creating Age Groups and Family Size Features in Titanic Dataset

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