Understand Big O Notation in Python
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About this course
In this 1-hour long project, you will gain first-hand experience using Python to model algorithmic efficiency tradeoffs. By implementing simulations of real-world systems using Big O notation, you will be able to quantify performance impacts of technical and business decisions. This will prepare you to advocate the importance of scale efficiency in data systems you design and maintain.
What you'll learn
- understand Big O notation
- apply Big O notation to real-world scenarios
- model algorithmic efficiency in Python
Course objectives
- learn to quantify performance impacts of technical decisions
- gain experience in advocating for scale efficiency
Skills you'll gain
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