Understand how to store, organize, and process data efficiently with algorithms.
Learn what data structures and algorithms are, why they are important, and how they impact program performa...
Understand Big-O notation and how to analyze algorithm efficiency.
Learn about arrays, indexing, insertion, deletion, and traversal.
Explore how dynamic arrays like vectors and ArrayLists work internally.
Understand singly linked lists, nodes, and traversal operations.
Learn about linked lists with two-way connections and circular references.
Study stacks, their operations (push, pop, peek), and implementation using arrays and linked lists.
Learn queues, enqueue/dequeue operations, and their types (simple, circular, priority).
Understand recursive problem-solving and how backtracking works.
Introduction to searching and linear vs. binary search techniques.
Learn how to efficiently search sorted data using binary search.
Understand BST properties and how to search, insert, and delete nodes.
Learn what graphs are and how they are represented (adjacency list/matrix).
Understand breadth-first and depth-first search algorithms.
Learn shortest path finding in weighted graphs.
Learn how to find MST using Prim’s and Kruskal’s algorithms.
Understand overlapping subproblems and optimal substructure concepts.
Study classic DP problems like Fibonacci, Knapsack, and Longest Subsequence.
Learn how greedy algorithms make locally optimal choices at each step.
Understand divide and conquer technique with examples like merge sort, quick sort.
Learn backtracking using examples like N-Queens and Sudoku solver.
Summarize complexities of all major algorithms and data structures.
Explore how DSA concepts are applied in software systems, compilers, and databases.
Compete, Learn & Win exciting prizes.