Big O Notation (Time Complexities)

In computer science, Big O notation is used to classify algorithms according to how their running time increases as the input size grows. Big O notation formalises the notion of “how long an algorithm takes to run”. We use it to describe the worst-case runtime. 

By taking this course, you can optimise your code to be more efficient. This course will also help you understand why code can take a lot longer to run if you do it wrong!

After completing this course, students will be able to:  

• Identify the time complexity of an algorithm on a graph 
• Explain why the time complexity of an algorithm is given a specific label 

1. O(1) 

2. O(log n) 

3. O(n) 

4. O(n2) 

5. O(n log n) 

• Interpret algorithms to determine their time complexity