A Base das Entrevistas de Algoritmo (BIG O)

The same code that seems instantaneous with little data can crash when the input grows. In this first episode of the data structures series, you'll understand how data structures, algorithms, and Big O connect. The idea isn't to memorize names, but to learn to see what really matters: which operation dominates the problem, how the cost grows with the size of the input, and what trade-offs appear between time and memory. We'll go through O(1), O(n), O(log n), O(n²), best case, worst case, average case, and how to use this reasoning to read technical interview problems more clearly. If you want to choose data structures with more confidence and stop guessing complexity in interviews, this video is the starting point. #DataStructures #BigO #Algorithms #Programming #TechnicalInterview