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  1. Arrays and Strings:

    • Understanding arrays, strings, and their operations.
    • Working with multidimensional arrays.

  2. Linked Lists:

    • Singly linked lists, doubly linked lists, and circular linked lists.
    • Basic operations (insertion, deletion, traversal).

  3. Stacks and Queues:

    • Implementing stacks and queues using arrays and linked lists.
    • Operations like push, pop, enqueue, and dequeue.

  4. Trees and Binary Trees:

    • Understanding different types of trees (binary trees, binary search trees, AVL trees, etc.).
    • Traversing algorithms (in-order, pre-order, post-order).
    • Tree balancing techniques.

  5. Graphs:

    • Understanding graph representation (adjacency matrix, adjacency list).
    • Basic graph algorithms (BFS, DFS).
    • Shortest path algorithms (Dijkstra's, Bellman-Ford).

  6. Sorting and Searching:

    • Common sorting algorithms (e.g., Bubble Sort, Selection Sort, Merge Sort, Quick Sort).
    • Binary search and its variations.

  7. Hashing:

    • Understanding hash functions and collision resolution techniques.
    • Working with hash maps.

  8. Dynamic Programming:

    • Solving problems using bottom-up and top-down approaches.
    • Understanding memoization and tabulation.

  9. Recursion:

    • Understanding recursive functions and solving problems recursively.

  10. Greedy Algorithms:

    • Understanding the greedy approach and its application in solving optimization problems.

  11. Bit Manipulation:

    • Working with bitwise operations.
    • Solving problems related to bitwise manipulation.

  12. Complexity Analysis (Big O Notation):

    • Analyzing the time and space complexity of algorithms.

  13. Space and Time Trade-offs:

    • Understanding when to optimize for space or time, depending on the problem.

  14. Problem Solving Skills:

    • Practicing coding problems on platforms like LeetCode, HackerRank, and GeeksforGeeks.