Big-O notation is the language interviewers use to judge your code without ever running it. In a quant coding round nobody has time to feed your function a million rows of market data and watch the clock. Instead they read your solution, work out how its cost grows as the input grows, and decide in seconds whether it survives at scale. This is the foundation lesson for the course: every later lesson reports the cost of its data structures and algorithms in this notation. Here we cover what Big-O measures, the handful of complexity classes you must recognize on sight, how to read the cost straight off the code, and two of our interview questions (All Pairs and Find the Missing Number) worked end to end with a slow version and a fast version side by side.
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