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Learning Paths / Learn Data Structures & Algorithms

data-structures
intermediate
14h estimated

Learn Data Structures & Algorithms

Master the DSA toolkit for interviews and real work: core data structures plus searching, sorting, and problem-solving patterns.

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Linear Structures

  1. 1

    Arrays

    Contiguous, index-based collections with fast random access

  2. 2

    Linked Lists

    Node-based sequences with cheap inserts and removals

  3. 3

    Stacks

    Last-in, first-out structure for ordered processing

  4. 4

    Queues

    First-in, first-out structure for fair, ordered processing

Hashing & Trees

  1. 1

    Hash Tables

    Key-value storage with average O(1) lookup and insertion

  2. 2

    Trees

    Hierarchical node structures like binary search trees

  3. 3

    Heaps

    Priority-ordered trees for fast access to the smallest item

  4. 4

    Graphs

    Networks of nodes and edges modeling relationships

Complexity

  1. 1

    Big-O Notation

    Measure how an algorithm's time and space grow as input size increases

Searching & Sorting

  1. 1

    Searching

    Find a value in a collection using linear or binary search

  2. 2

    Sorting

    Arrange elements in order using bubble sort and merge sort

  3. 3

    Binary Search Patterns

    Apply binary search beyond sorted arrays to find boundaries and answers

Techniques

  1. 1

    Recursion

    Solve problems by having a function call itself on smaller inputs

  2. 2

    Two Pointers

    Use two indices moving through a sequence to solve problems in linear time

  3. 3

    Sliding Window

    Track a contiguous range in a sequence to answer subarray questions efficiently

  4. 4

    Greedy

    Build a solution by always making the locally optimal choice

  5. 5

    Dynamic Programming

    Solve overlapping subproblems once and reuse the results

  6. 6

    Graph Traversal

    Visit every reachable node in a graph using breadth-first or depth-first search