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Data Science Beginner

Data Cleaning

A comprehensive, beginner-friendly guide to learning Data Cleaning. Master the fundamentals and build real-world projects.

20 chapters 1h 40m 4.6 (175)
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What you'll learn

  • Introduction to Data Cleaning
  • Understanding Dirty Data
  • Installing Python and Data Cleaning Tools
  • Working with CSV, Excel, and JSON Files
  • Data Types and Data Formatting
  • Handling Missing Values
  • Removing Duplicate Data
  • Detecting and Handling Outliers

Course content

20 chapters Β· 1h 40m
  1. 1 Introduction to Data Cleaning 5 min
  2. 2 Understanding Dirty Data 5 min
  3. 3 Installing Python and Data Cleaning Tools 5 min
  4. 4 Working with CSV, Excel, and JSON Files 5 min
  5. 5 Data Types and Data Formatting 5 min
  6. 6 Handling Missing Values 5 min
  7. 7 Removing Duplicate Data 5 min
  8. 8 Detecting and Handling Outliers 5 min
  9. 9 String Cleaning and Text Processing 5 min
  10. 10 Date and Time Cleaning 5 min
  11. 11 Data Validation Techniques 5 min
  12. 12 Cleaning Data with Pandas 5 min
  13. 13 Cleaning Data with SQL 5 min
  14. 14 Data Transformation and Standardization 5 min
  15. 15 Exploratory Data Analysis for Cleaning 5 min
  16. 16 Automating Data Cleaning Pipelines 5 min
  17. 17 Real-World Data Cleaning Projects 5 min
  18. 18 Performance Optimization for Large Datasets 5 min
  19. 19 Data Cleaning Interview Preparation 5 min
  20. 20 Final Projects and Real-World Applications 5 min