Data Structures
Array
- Introduction to Arrays
- Representation of Arrays
- Array Operations:
- Traversal, Insertion,
- Deletion, Searching
- Multi-dimensional
- Arrays (2D, 3D arrays)
Programming Courses
Data Structure & Algorithm
Have you ever thought of Learning Data Structure & Algorithm?
Based on 99 Reviews
- Duration : 1 Month / 3 Months / 6 Months
- Language: English
- Certificate of Completion
Data Structure & Algorithm Course Overview
Build a solid foundation in problem-solving and coding efficiency with our Data Structures and Algorithms (DSA) Course, designed for both beginners and experienced programmers. DSA is a critical skill for cracking coding interviews, optimizing software performance, and mastering competitive programming.
This course covers essential data structures like arrays, linked lists, stacks, queues, trees, graphs, and hash tables, as well as algorithms for sorting, searching, recursion, dynamic programming, and greedy techniques. You’ll learn to write clean, efficient, and scalable code while solving real-world problems and participating in coding challenges.
Whether you’re preparing for technical interviews, improving your programming logic, or aiming to excel in competitive coding, this course provides the practical knowledge and confidence to tackle complex problems with ease.
Key Features
Globally Recognised Certification
100% online and Self-paced learning
Access to 4 Gamified Practise Platforms
Dedicated doubts Session
Full lifetime access to all content
7 Days refund Policy
Course Topics You will Learn
Matrix/Grid
- Introduction to Matrices
- Representation and Operations (addition, multiplication)
- Traversing 2D / 3D arrays
String
- Introduction to Strings
- String Representation
- String Operations (concatenation, comparison, searching)
Stack
- Definition and Operations (Push, Pop, Peek)
- Stack Implementations using Arrays and Linked Lists
Queue
- Definition and Operations (Enqueue, Dequeue, Front, Rear)
- Types of Queues: Simple Queue, Circular Queue, Priority Queue, Double-ended Queue
Linked List
- Introduction to Linked Lists (Singly, Doubly, Circular)
- Operations: Insertion, Deletion, Traversing
- Reversing a Linked List,
- Detecting and Removing Loops
Tree
- Introduction to Trees
- Tree Terminology: Root, Leaf, Parent, Child, Depth, Height
- Binary Trees and Traversals: Inorder, Preorder, Postorder
- Binary Tree Operations (Insertion, Deletion, Searching)
- Balanced Trees: AVL Trees, Red-Black Trees
Binary Tree
- Properties of Binary Trees
- Binary Tree Traversals (Recursive and Iterative Approaches)
- Insertion, Deletion, Searching
Binary Search Tree (BST)
- Introduction to BST
- BST Operations: Search, Insert, Delete
- Balanced BST: AVL Tree, Red-Black Tree
Heap
- Introduction to Heaps:
- Max-Heap and Min-Heap
- Heap Operations: Insert, Delete, Heapify
- Heap Sort Algorithm
- Priority Queues
Graph
- Introduction to Graphs
- Graph Representations: Adjacency Matrix, Adjacency List
- Types of Graphs: Directed, Undirected, Weighted,
- Unweighted
Graph Traversals: BFS (Breadth-First Search), DFS (Depth-First Search)
Algorithms
Complexity Theory
- Time Complexity: Big-O Notation, Best, Worst, Average Case
- Space Complexity: Analyzing Space
- Usage of Algorithms
- P vs NP Problem
- NP-Complete and NP-Hard Problems
- Approximation Algorithms
Searching Algorithms
- Linear Search
- Binary Search (Iterative and Recursive)
- Exponential Search
- Interpolation Search
Sorting
- Introduction to Sorting Algorithms
- Elementary Sorting Algorithms: Bubble Sort, Selection Sort, Insertion Sort
- Efficient Sorting Algorithms: Merge Sort, Quick Sort, Heap Sort
- Non-Comparative Sorting: Counting Sort, Radix Sort
Dynamic Programming
- Introduction to Dynamic Programming
- Memoization vs Tabulation
- Classic DP Problems: Fibonacci, Knapsack Problem, Longest Common Subsequence
- Optimal Substructure and Overlapping Subproblems
- Applications of DP: Coin Change, Matrix Chain Multiplication
Greedy Algorithms
- Introduction to Greedy Algorithms
- Greedy Choice Property and Optimal Substructure
- Classic Greedy Problems: Activity Selection, Huffman Coding, Fractional Knapsack
Binary Search
- Introduction to Binary Search
- Binary Search on Sorted Arrays
- Variations: Binary Search on Rotated Arrays, Searching in Infinite Arrays
Backtracking
- Introduction to Backtracking Algorithms
- Backtracking Problems: N-Queens, Sudoku Solver, Rat in a Maze
- Subset Sum Problem
- Applications in Puzzles and Combinatorial Problems
Recursion
- Introduction to Recursion
- Base Case and Recursive Case
- Recursive Functions: Factorial, Fibonacci Sequence, Tower of Hanoi
- Recursion vs Iteration: Advantages and Disadvantages
Divide and Conquer
- Introduction to Divide and Conquer Algorithms
- Problem Solving with Divide and Conquer: Merge Sort, Quick Sort, Binary Search
- Strassen’s Matrix Multiplication Algorithm
Hashing
- Introduction to Hashing and Hash Functions
- Hash Table Implementations
- Collision Resolution Techniques: Separate Chaining, Open Addressing
- Applications of Hashing: Caching, Hash Maps, Hash Sets
This Course Include
- Language: English
- Duration : 1 Month / 3 Months / 6 Months
- Learning Mode: At Center ( Only Offline Classes )
- Jurisdiction: Nationwide
- Certificate of Completion
Eligibility Criteria
- Learner should preferably a std. 10th Pass student (Not Compulsory)
- It is desirable that Learner should have done MS-CIT Course (Not Compulsory)
Premium Course
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Who will Teach You
Anjali Arora
App Developer ( IBM )
About Ms. Anjali Arora
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