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C++ Data Structures & Algorithms
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Module 1
Complexity Analysis and Core Concepts
1
Big-O Analysis of Iterative Algorithms
Determine the time complexity of iterative algorithms using Big-O notation.
2
Understanding Space Complexity
Determine the space complexity of an algorithm.
3
Analyzing Algorithm Complexities
Compare algorithms by analyzing their best-case, worst-case, and average-case complexity.
4
Time-Space Trade-offs in Data Structures
Analyze time-space trade-offs in simple scenarios, such as using a hash table for faster lookup.
5
STL Vector and String for Algorithmic Problems
Use C++ STL vector and string classes effectively in algorithmic problems.
6
Two-Pointer Technique for Arrays and Strings
Apply the two-pointer technique to solve array and string problems.
7
Sliding Window Technique for Subarrays and Substrings
Apply the sliding window technique to solve subarray and substring problems.
8
Spiral Matrix Traversal
Traverse a 2D matrix in spiral order.
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