🍉Data Structures

1. Arrays:

   • Understand the concept of arrays, their characteristics, and memory representation.

   • Learn about array operations such as insertion, deletion, searching, and sorting.

   • Implement algorithms and programs involving arrays to gain hands-on experience.

2. Linked Lists:

   • Study different types of linked lists: singly linked lists, doubly linked lists, and circular linked lists.

   • Learn about linked list operations like insertion, deletion, traversal, and reversal.

   • Implement linked lists and solve problems involving them.

3. Stacks:

   • Understand the LIFO (Last-In-First-Out) principle behind stacks.

   • Study stack operations like push, pop, peek, and isEmpty.

   • Implement a stack using arrays or linked lists and solve problems that require stack-based algorithms.

4. Queues:

   • Understand the FIFO (First-In-First-Out) principle behind queues.

   • Study queue operations like enqueue, dequeue, peek, and isEmpty.

   • Implement a queue using arrays or linked lists and solve problems that require queue-based algorithms.

5. Trees:

   • Learn about the basic tree terminology: nodes, edges, root, parent, child, leaf, etc.

   • Study different types of trees: binary trees, binary search trees, balanced trees (AVL, Red-Black), and heap.

   • Understand tree traversal algorithms: preorder, inorder, postorder, and level order.

   • Implement trees, perform traversals, and solve problems involving trees.

6. Graphs:

   • Understand the concepts of graphs, vertices, and edges.

   • Study different types of graphs: directed, undirected, weighted, and cyclic graphs.

   • Learn graph traversal algorithms: depth-first search (DFS) and breadth-first search (BFS).

   • Implement graphs and traverse them using DFS and BFS algorithms.

   • Study graph algorithms like shortest path algorithms (Dijkstra's, Bellman-Ford), and minimum spanning tree algorithms (Prim's, Kruskal's).

7. Hash Tables:

   • Understand the concept of hashing and its applications.

   • Study hash table operations: insert, delete, and search.

   • Learn collision resolution techniques: chaining and open addressing.

   • Implement a hash table and solve problems involving hash-based algorithms.

8. Advanced Data Structures:

   • Explore more advanced data structures like heaps, trie, segment tree, and AVL trees.

   • Understand their characteristics, operations, and use cases.

   • Implement these data structures and solve problems that require their usage.

Structured Plan:

1. Start with arrays and practice basic array operations.

2. Move on to linked lists and implement basic operations like insertion and deletion.

3. Study and implement stack operations like push, pop, and peek.

4. Learn about queues and implement queue operations like enqueue and dequeue.

5. Dive into trees, understand the basic concepts, and implement tree traversals.

6. Explore graphs, understand their representations, and implement traversal algorithms.

7. Study hash tables, implement basic operations, and understand collision resolution techniques.

8. Delve into advanced data structures and implement them while solving problems.

It's essential to reinforce your learning with practice, coding exercises, and real-world projects involving data structures. Additionally, refer to relevant textbooks, online resources, and programming platforms that provide interactive coding challenges to deepen your understanding of each data structure.