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Algorithms Complexity

Track :

Programming

Lessons no : 76

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What will you learn in this course?
  • Understand and analyze algorithmic complexity using Big O, Big Theta, and Big Omega notations for efficient problem-solving
  • Evaluate the performance of algorithms based on input size and computational resources in real-world applications
  • Identify and compare the time and space complexities of various algorithms across different problem domains
  • Apply asymptotic analysis techniques to optimize algorithms for scalability and efficiency in software development
  • Determine the most suitable algorithmic approach for specific problems by assessing complexity trade-offs
  • Interpret complexity functions to predict algorithm behavior and performance in practical scenarios
  • Utilize complexity analysis to improve algorithm design, reducing runtime and memory usage in large-scale systems
  • Assess the impact of algorithmic complexity on system performance and computational resource management

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Lessons | 76
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KaSo

I learned new and interesting informations thank you 2023-07-08

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Algorithmic complexity is concerned about how fast or slow particular algorithm performs. We define complexity as a numerical function T(n) - time versus the input size n. We want to define time taken by an algorithm without depending on the implementation details.