1. Arrays

• Introduction to Arrays

• One-Dimensional and Multi-Dimensional Arrays

• Operations: Insertion, Deletion, Traversal, Searching, Sorting

• Applications of Arrays

2. Linked Lists

• Introduction to Linked Lists

• Types: Singly, Doubly, and Circular Linked Lists

• Operations: Insertion, Deletion, Traversal, Searching

• Applications of Linked Lists

3. Stacks

• Introduction to Stacks

• Stack Operations: Push, Pop, Peek

• Implementation using Arrays and Linked Lists

• Applications: Expression Evaluation, Parsing, Backtracking

4. Queues

• Introduction to Queues

• Types: Linear, Circular, Priority, and Double-Ended Queues

• Operations: Enqueue, Dequeue, Peek

• Implementation using Arrays and Linked Lists

• Applications: Scheduling, Buffering

1. Trees

• Introduction to Trees

• Binary Trees: Properties, Types, and Traversal (Inorder, Preorder, Postorder, Level Order)

• Binary Search Trees (BST): Insertion, Deletion, Searching

• Balanced Trees: AVL Trees, Red-Black Trees

• Applications: File Systems, Hierarchical Data

2. Graphs

• Introduction to Graphs

• Types: Directed, Undirected, Weighted, Unweighted

• Representation: Adjacency Matrix, Adjacency List

• Traversal Algorithms: Depth-First Search (DFS), Breadth-First Search (BFS)

• Applications: Social Networks, Maps, Recommendation Systems

3. Hashing

• Introduction to Hashing

• Hash Functions and Collision Resolution Techniques

• Hash Tables: Insertion, Deletion, Searching

• Applications: Databases, Caching, Cryptography

1. Heaps

• Introduction to Heaps

• Types: Min-Heap, Max-Heap

• Operations: Insertion, Deletion, Heapify

• Applications: Priority Queues, Heap Sort

2. Advanced Trees

• B-Trees and B+ Trees: Properties and Applications in Databases

• Trie (Prefix Tree): Insertion, Deletion, Searching

• Applications: Autocomplete, Spell Checking

3. Advanced Graphs

• Shortest Path Algorithms: Dijkstra’s Algorithm, Bellman-Ford Algorithm, Floyd-Warshall Algorithm

• Minimum Spanning Tree (MST): Kruskal’s Algorithm, Prim’s Algorithm

• Topological Sorting

• Applications: Network Routing, Project Scheduling

1. Sorting Algorithms

• Bubble Sort, Selection Sort, Insertion Sort

• Merge Sort, Quick Sort, Heap Sort

• Radix Sort, Counting Sort, Bucket Sort

2. Searching Algorithms

• Linear Search, Binary Search

• Interpolation Search, Exponential Search

3. Dynamic Programming

• Introduction to Dynamic Programming

• Problems: Fibonacci Series, Knapsack Problem, Longest Common Subsequence (LCS)

4. Greedy Algorithms

• Introduction to Greedy Algorithms

• Problems: Fractional Knapsack, Activity Selection, Huffman Coding

5. Divide and Conquer

• Introduction to Divide and Conquer

• Problems: Merge Sort, Quick Sort, Closest Pair of Points

1. Applications of Data Structures

• Databases: Indexing, Query Optimization

• Operating Systems: File Systems, Memory Management

• Artificial Intelligence: Search Algorithms, Decision Trees

• Networking: Routing Algorithms, Packet Filtering

2. Hands-On Projects

• Building a File System using Trees

• Implementing a Social Network Graph using Graphs

• Designing a Search Engine using Hashing and Sorting

1. Programming Languages

• Python, Java, C++

2. Development Tools

• IDEs, Debuggers, Version Control Systems (Git)

3. Visualization Tools

• Graphviz, Matplotlib

1. Coding Challenges

• Practice solving coding problems commonly asked in technical interviews.

2. Interview Strategies

• Learn strategies to approach and solve complex problems efficiently.

3. Competitive Programming

• Gain confidence in tackling competitive programming challenges.