Intro to Data Cleaning and Preprocessing with Titanic | CodeSignal Learn

Journey into Data Science with PythonIntro to Data Cleaning and Preprocessing with Titanic

Intro to Data Cleaning and Preprocessing with Titanic

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.

Lessons and practices

Lesson 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

Lesson 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

Lesson 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

Lesson 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

Lesson 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

Lesson 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

Interested in this course? Learn and practice with Cosmo!

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