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Data Structures and Algorithms
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Module 1
Complexity Analysis and Problem-Solving Strategy
Iterative Algorithm Complexity with Big O
Calculate time complexity of iterative algorithms using Big O notation.
2
Analyzing Divide-and-Conquer Time Complexity
Estimate time complexity of common divide-and-conquer algorithms.
3
Understanding Space Complexity
Analyze space complexity, distinguishing between input size, auxiliary space, and call stack usage.
4
Understanding Time-Space Tradeoffs
Identify and articulate time-space tradeoffs in different algorithmic approaches.
5
Understanding Common Complexity Classes
Recognize common complexity classes: O(1), O(log n), O(n), O(n log n), O(n²), O(2^n).
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Core Sequential Data Structures