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Discover reviews on "dsa" based on Reddit discussions and experiences.

Last updated: January 30, 2025 at 12:01 AM
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Summary of Reddit Comments on DSA

DSA

  • DSA (Data Structures and Algorithms) is essential for job placements and internships in the tech field. It is a fundamental subject that tests problem-solving skills.
  • Pros:
    • DSA provides a standardized measure to evaluate problem-solving abilities in candidates.
    • Helps in developing problem-solving skills and understanding important concepts.
    • Useful for technical job interviews, especially in large tech companies like FAANG.
    • Integral for building software, especially in data-intensive tasks or system design.
  • Cons:
    • Some view DSA as impractical or overemphasized, with the belief that real-world projects are more beneficial at times.
    • The focus on DSA in interviews may overshadow other important skills like system design and architecture.
    • Can lead to burnout and stress, especially when extensively practiced for job interviews.
  • Some users suggest starting DSA early in college, following platforms like Leetcode, Codechef, or CodeForces, and balancing with system design components later on.
  • Competitive Programming (CP) is seen as a complement to DSA, testing problem-solving in a contest format with platforms like CodeForces and AtCoder.
  • Users stress the importance of understanding the practical applications of DSA, balancing it with real-world projects, and building a strong software engineering foundation.
  • The distinction between DSA's theoretical focus and CP's logical and contest-oriented format is highlighted.

Advice for Learning DSA

  • Recommended resources include Leetcode, GeeksforGeeks, CodeForces, Codechef, AtCoder, and InterviewBit for DSA and CP practice.
  • Additional resources like MIT and Princeton courses, Algoritms by Sedgewick and Wayne, and MOOC.fi for C/C++ learning are also suggested.
  • Starting DSA early in college is advisable to prepare for job placements and internships.
  • Complexity differences between CP and DSA are noted, with CP being more logical and application-based, while DSA is often theoretical and focused on explicit questions like Leetcode.
  • Suggestions for learning C++ and mastering the standard template library (STL) are provided for aspiring CP enthusiasts.
  • Users encourage a practical approach to DSA, emphasizing problem-solving and real-world applications over theoretical knowledge.

This summary provides insights into the significance of DSA in the tech industry, tips for learning, and balancing DSA practice with real-world projects to build a strong software engineering foundation.

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