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Data Science Beginner

Pandas & NumPy

A comprehensive, beginner-friendly guide to learning Pandas & NumPy. Master the fundamentals and build real-world projects.

30 chapters 2h 30m 4.8 (136)
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What you'll learn

  • Introduction to Data Science, Pandas, and NumPy
  • Installing Python, NumPy, and Pandas
  • NumPy Arrays Basics
  • NumPy Array Operations
  • NumPy Indexing and Slicing
  • NumPy Mathematical Functions
  • NumPy Broadcasting and Vectorization
  • NumPy Random Module

Course content

30 chapters · 2h 30m
  1. 1 Introduction to Data Science, Pandas, and NumPy 5 min
  2. 2 Installing Python, NumPy, and Pandas 5 min
  3. 3 NumPy Arrays Basics 5 min
  4. 4 NumPy Array Operations 5 min
  5. 5 NumPy Indexing and Slicing 5 min
  6. 6 NumPy Mathematical Functions 5 min
  7. 7 NumPy Broadcasting and Vectorization 5 min
  8. 8 NumPy Random Module 5 min
  9. 9 Introduction to Pandas 5 min
  10. 10 Pandas Series and DataFrames 5 min
  11. 11 Reading and Writing Data Files 5 min
  12. 12 Data Selection and Filtering 5 min
  13. 13 Data Cleaning in Pandas 5 min
  14. 14 Handling Missing Data 5 min
  15. 15 Data Transformation and Manipulation 5 min
  16. 16 GroupBy and Aggregation 5 min
  17. 17 Merging and Joining DataFrames 5 min
  18. 18 Working with Dates and Time Series 5 min
  19. 19 Data Visualization with Pandas 5 min
  20. 20 Advanced NumPy Concepts 5 min
  21. 21 Advanced Pandas Operations 5 min
  22. 22 Exploratory Data Analysis (EDA) 5 min
  23. 23 Statistical Analysis with Pandas and NumPy 5 min
  24. 24 Working with Large Datasets 5 min
  25. 25 Pandas with SQL Databases 5 min
  26. 26 Preparing Data for Machine Learning 5 min
  27. 27 Real-World Data Science Projects 5 min
  28. 28 Pandas and NumPy Interview Preparation 5 min
  29. 29 Performance Optimization in Pandas and NumPy 5 min
  30. 30 Final Projects and Real-World Applications 5 min