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Data Science Fundamentals with Python

Data Science Fundamentals

Read the introduction to this course.

Chapters

  1. Basic math, variables and the print and input functions
  2. Comparisons, the if statement and string concatenation and methods
  3. Concatenation and string methods
  4. Lists (basics)
  5. The for statement
  6. Advanced use of lists: methods and slicing
  7. The while statement
  8. Working with files
  9. F-strings
  10. Dicts (basics)
  11. Nested dicts
  12. JSON
  13. HTTP API's
  14. Displaying images and HTML in Jupyter Notebooks
  15. Printing complex data types
  16. Pandas (basics)
  17. Pandas: combining data sets using merge() and concat()
  18. Pandas: importing structured data formats
  19. Pandas: filtering and sorting data
  20. Pandas: advanced ways to transform data with apply()
  21. Pandas: plots and visualisations
  22. Pandas: working with temporal data
  23. Accessing the Reddit API using the praw library
  24. Functions
  25. Web scraping with BeautifulSoup

Credits

This course was developed by Hay Kranen with generous feedback from Jonas Moons. Logo by Ranganath Krishnamani.