Learn to write efficient code by analyzing NBA data.


  • Learn the importance of modularity and abstraction when working with algorithms.
  • Learn the difference between constant and linear time algorithms.
  • Learn the notation and framework for time complexity.

Mission Outline

1. What is an algorithm?
2. Implementing an Algorithm
3. The Importance of Modularity and Abstraction
4. Linear Search with Modular Code
5. What Makes an Algorithm Smart?
6. Constant Time Algorithms
7. Exercise: Recognizing Constant Time Algorithms
8. A Common Pitfall
9. Linear Time Algorithms
10. Some Other Algorithms
11. Notation for Time Complexity
12. Why Time Complexity Matters
13. Takeaways

Course Info:

Data Structures and Algorithms


The average completion time for this course is 10-hours.

This course requires a premium subscription. This course includes five paid missions, and one guided project. It is the 26th course in the Data Scientist in Python path.


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