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Become a skilled software engineer
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Module 1
Complexity Analysis Foundations
1
Understanding Big O Notation
Explain what Big O notation represents and why it matters for algorithm analysis
2
Analyzing Loop Time Complexity
Calculate the time complexity of simple loops and nested loops
3
Auxiliary Space Complexity
Calculate the space complexity of algorithms based on auxiliary data structures used
4
Understanding Common Complexity Classes
Compare common complexity classes (O(1), O(log n), O(n), O(n log n), O(n²), O(2ⁿ))
5
Data Structure Operations: Time Complexity
Identify the time complexity of basic operations on arrays, hash tables, and linked lists
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