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Data Science Beginner

Python for Data Science

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

30 chapters 2h 30m 4.8 (218)
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What you'll learn

  • Introduction to Python for Data Science
  • Installing Python and Data Science Environment
  • Python Basics for Data Science
  • Variables, Data Types, and Operators
  • Conditional Statements and Loops
  • Functions and Modules in Python
  • Working with Strings and Lists
  • Tuples, Sets, and Dictionaries

Course content

30 chapters Β· 2h 30m
  1. 1 Introduction to Python for Data Science 5 min
  2. 2 Installing Python and Data Science Environment 5 min
  3. 3 Python Basics for Data Science 5 min
  4. 4 Variables, Data Types, and Operators 5 min
  5. 5 Conditional Statements and Loops 5 min
  6. 6 Functions and Modules in Python 5 min
  7. 7 Working with Strings and Lists 5 min
  8. 8 Tuples, Sets, and Dictionaries 5 min
  9. 9 File Handling in Python 5 min
  10. 10 Introduction to NumPy 5 min
  11. 11 NumPy Arrays and Operations 5 min
  12. 12 NumPy Broadcasting and Vectorization 5 min
  13. 13 Introduction to Pandas 5 min
  14. 14 Pandas Series and DataFrames 5 min
  15. 15 Data Cleaning with Pandas 5 min
  16. 16 Data Analysis and Aggregation 5 min
  17. 17 Working with CSV, Excel, and JSON Data 5 min
  18. 18 Data Visualization with Matplotlib 5 min
  19. 19 Statistical Visualization with Seaborn 5 min
  20. 20 Exploratory Data Analysis (EDA) 5 min
  21. 21 Introduction to Machine Learning 5 min
  22. 22 Data Preprocessing for Machine Learning 5 min
  23. 23 Regression Algorithms 5 min
  24. 24 Classification Algorithms 5 min
  25. 25 Model Evaluation Techniques 5 min
  26. 26 Working with APIs and Web Data 5 min
  27. 27 Real-World Data Science Projects 5 min
  28. 28 Python for Data Science Interview Preparation 5 min
  29. 29 Advanced Data Science Techniques 5 min
  30. 30 Final Projects and Real-World Applications 5 min