#data_science

  1. 1. Boolean values
  2. 1D array
  3. Aggregate Functions in Python
  4. Applications of Data Science
  5. Array Functions and Methods in NumPy
  6. Big Data
  7. Case Study - A Journey to Becoming a Data Scientist
  8. Categories of Tasks (for Data Science)
  9. Cloud Introduction
  10. Create a simple DataFrame
  11. Data Integration Platforms
  12. DataSci Method
  13. Different Types of File Formats in Data Science
  14. Getting Hired in Data Science
  15. Getting started with the Model Asset Exchange and the Data Asset Exchange
  16. Hands-On Lab: Branching and Merging
  17. Introduction to Git & GitHub
  18. Introduction to Watson Studio
  19. lets import the reader from the CSV module
  20. Libraries of Data Science
  21. Linking GitHub to Watson Studio
  22. LIST example
  23. Machine Learning Models
  24. Metadata and Metadata Management
  25. Methods in Pandas
  26. ORIGINAL LIST
  27. Regression
  28. Report Structure in Data Science
  29. Repositories in GitHub
  30. Review existing Jupyter Notebooks
  31. Roadmap to your Data Science Journey
  32. Simple SELECT
  33. successes (conversions), observations (visitors)
  34. This is a heading
  35. Watson Studio Project with Jupyter Notebooks
  36. Web Scraping - A Key Tool in Data Science
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