Скачать или смотреть 03 Amortization, Memory Complexity & NP-Hard Concepts | AlgoZenith DSA Lecture

Amortization, Memory Complexity & NP-Hard Concepts | Complete AlgoZenith Lecture

This lecture explores three advanced and interrelated topics in Algorithm Analysis — Amortized Analysis, Memory (Space) Complexity, and NP-Hard Problems. Each of these topics forms a crucial part of advanced DSA and computational complexity theory, helping you evaluate and design efficient algorithms.

Topics Covered:
• Amortized Analysis — aggregate, accounting, and potential methods
• Real-world examples: dynamic arrays, stack operations, and hashing
• Memory (Space) Complexity — analyzing auxiliary and recursive space
• Understanding P, NP, NP-Complete, and NP-Hard classifications
• Polynomial-time reductions and problem intractability
• Classic NP-Hard problems — Knapsack, SAT, TSP

Learning Outcomes:
• Perform accurate time and space efficiency analysis
• Understand computational problem classifications and their boundaries
• Strengthen your foundation in advanced algorithmic theory

Ideal For: Students preparing for GATE, placements, coding interviews, and competitive programming.

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