Big O and Time Complexity

Understand the concept of time complexity and Big O in this comprehensive guide. Learn how to evaluate the performance of an algorithm and describe it using Big O Notation. Learn how to identify algorithms with time complexities of O(1), O(log N), O(N), O(n^2), and O(b^n). Each time complexity is described using visuals as well as breakpoints and code examples.

Enhance your programming knowledge and deepen your understanding of Big O with the fundamentals presented in this video. Use it as a foundation for further learning and practice through our accompanying workbook.

Workbook: https://bit.ly/workbookBigO
Courses: https://www.udemy.com/user/learn-the-...
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00:00 Big O and Time Complexity
01:52 O(1)
03:56 O(n)
07:04 O(log n)
09:37 O(n^2)
14:03 O(b^n)
17:15 Workbook