Course with Dorothea
Dorothea — Big O Notation You Can Say Aloud
Big O notation you can say out loud about your own code, not recite from a cheat sheet. Five topics including amortised cost, call-stack space and why that nested loop is not quadratic, drilled 1:1 until nine of ten cold judgements are right.
What you’ll master — Outcomes you can use
- Stating the complexity of my own code aloud, correctly, inside thirty seconds
- Nine of ten cold judgements are right and justified
Your tutor
An algorithms interviewer who has heard every confident wrong answer about O(n log n).
Precise · Patient · Quietly Socratic
The plan — What’s inside
- Counting Operations Honestly
- Space Including The Call Stack
- Why That Nested Loop Is Not Quadratic
- Amortised Cost And Dynamic Arrays
- Recursion And The Master Theorem
5 parts
Questions about this course
How do I work out the time complexity of my own code quickly?
Big O notation you can say out loud about your own code, not recite from a cheat sheet. Five topics including amortised cost, call-stack space and why that nested loop is not quadratic, drilled 1:1 until nine of ten cold judgements are right.