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Learning Data Structures
·
Module 1
Foundations: Complexity & Recursion
1
Big-O Complexity of Iterative and Recursive Algorithms
Calculate the time complexity of iterative and recursive algorithms using Big-O notation.
Analyzing Space Complexity: Auxiliary Space and Recursion Stack
Analyze the space complexity of an algorithm, considering both auxiliary space and the recursion stack.
3
Analyzing Recursive Algorithms with Recurrence Relations and the Master Theorem
Formulate recurrence relations for recursive algorithms and apply the Master Theorem to solve them.
4
Tracing Recursive Functions with the Call Stack
Trace the execution of a recursive function on the call stack to understand its flow, base cases, and recursive steps.
5
Bitwise Operations for Array Problems
Apply bitwise operators (AND, OR, XOR, Left/Right Shift) to solve simple array problems like finding the single number.
6
Recursion: Factorial, Fibonacci, and Overlapping Subproblems
Implement basic recursive solutions for problems like factorial and Fibonacci, identifying overlapping subproblems.
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Arrays & Hashing