Pynex Logo

Phase 4: Data Science Essentials

Build the essential numerical and analytical foundation required for Artificial Intelligence. You will learn how to clean, manipulate, and analyze massive datasets using NumPy and Pandas, while building stunning visual charts and performing exploratory data analysis.

The curriculum is public. Reading these lessons requires access to the corresponding paid track. Compare access and pricing.

What will you learn?

Lessons and practice

  1. Lesson 1: Why NumPy Exists
  2. Lesson 2: Indexing, Slicing, and Reshaping
  3. Lesson 3: Broadcasting and Vectorized Operations
  4. NumPy Practice Exercises
  5. NumPy Cheatsheet
  6. NumPy — Interview Questions
  7. Lesson 1: What is a DataFrame?
  8. Lesson 2: Cleaning and Transforming Data
  9. Lesson 3: GroupBy, Merge & Pivot — Reshaping & Aggregating Data
  10. Pandas Practice Exercises
  11. Pandas Cheatsheet
  12. Pandas — Interview Questions
  13. Lesson 1: Why Visualise Data?
  14. Lesson 2: Practical Seaborn & Plot Selection — Crafting Insights
  15. Lesson 3: Chart Types — What to Use When & Why
  16. Data Science Visualization Practice Exercises
  17. Data Visualization — Cheatsheet
  18. Lesson 1: What is EDA?
  19. Lesson 2: Outlier Detection and Feature Insights
  20. Lesson 3: Correlation, Multivariate Analysis & EDA Report
  21. Lesson 4: Real-World EDA Capstone Walkthrough — From Dirty Data to Executive Report
  22. EDA Practice Exercises
  23. EDA Cheatsheet
  24. Lesson 1: What is Feature Engineering?
  25. Lesson 2: Feature Engineering Techniques — Encoding, Scaling & Creation
  26. Feature Engineering — Practice Exercises
  27. Lesson 1: Statistics Every Data Scientist Must Know
  28. Lesson 2: Distributions, Z-Scores & the Central Limit Theorem
  29. Lesson 2: Statistical Testing — Proving Your Results Are Real
  30. Statistics for Data Science — Practice Exercises
  31. Statistics for Data Science — Cheatsheet
  32. Statistics — Interview Questions
  33. Data Science Capstone Project

Explore the full Python to AI Engineer curriculum · Practice Python in the browser