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Competitive Programming

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Competitive Programming

This competitive programming curriculum covers a wide range of essential topics aimed at equipping learners with the skills needed to tackle complex problems efficiently. Starting with problem analysis and understanding time complexity, students delve into analyzing constraints, crucial for optimizing solutions.

Number theory concepts such as the Sieve of Eratosthenes, the Pigeonhole Principle, and Modular Arithmetic are explored, providing tools for handling integer-based problems effectively. Additionally, techniques like Binary Exponentiation and the Euclidean Theorem for GCD offer efficient solutions for mathematical challenges.

Arrays and Hashing, Sorting and Searching, and advanced algorithms like Two Pointers, Sliding Window, and Binary Search are covered to enhance problem-solving abilities. Recursion and Backtracking, pivotal for solving problems with recursive structures, are thoroughly studied.

Students then progress to understanding Trees and Graphs, both fundamental data structures for many algorithms. Advanced graph algorithms and dynamic programming techniques are introduced to tackle more intricate problems.

The curriculum also includes Range Queries, Interval Questions, and Miscellaneous topics like Policy-Based Data Structures (PBDS) and monotonic stacks, providing students with diverse tools to approach various problem types effectively. By mastering these concepts, students are well-prepared to excel in competitive programming competitions.

  1.  Problem Analysis and Time Complexity
      - Analyzing problem statements
      - Understanding time complexity
      - Analyzing constraints
      - Handling Big Integers in C++
  2.  Number Theory
      - Sieve of Eratosthenes
      - Pigeon Hole Principle
      - Modular Arithmetic
      - Binary Exponentiation
      - Euclidean Theorem for GCD
      - Binomial Coefficient

  3.  Arrays, Hashing and Priority Queues
      - Manipulating arrays
      - Utilizing hashing techniques
      - Custom comparators

  4.  Sorting and Searching
      - Sorting algorithms
      - Searching techniques

  5.  Two Pointers, Sliding Window, and Binary Search
      - Two pointers approach
      - Sliding window technique
      - Binary search algorithm

  6.  Recursion and Backtracking
      - Understanding recursion
      - Implementing backtracking algorithms

  7.  Trees
      - Tree data structure
      - Tree traversal algorithms

  8.  Graphs
      - Graph representation
      - Graph traversal algorithms
      - Connected Components
      - Cycles
  9. Advanced Graphs
    - Minimum Spanning Tree
      - Topological Sort
      - Strongly Connected Components
      - Disjoint Set Union

  10.  Dynamic Programming (DP)
      - DP techniques
      - Memoization and tabulation

  11.  Range Queries and Intervallic Questions
      - Solving range query problems
      - Handling interval-related questions

  12.  Miscellaneous Topics
      - Policy-Based Data Structures (PBDS)
      - Decompositions
      - Monotonic stacks
      - Binary Search on answer strategies



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Durations: 3 months Total Hours: 24+ Lectures: 2 Hours / Week Labs: 2 Hours / Week Age Group: 13-18 Years Skill Level: Advanced

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