Introduction to Data Structures

• Understanding the importance of data structures in computer science
• Exploring different types of data structures and their applications
• Comparing and contrasting different data structure implementations

Arrays

• Understanding arrays and their properties
• Exploring operations on arrays, such as insertion, deletion, and searching
• Analyzing time and space complexity of array operations

Linked Lists

• Understanding linked lists and their variants (singly linked list, doubly linked list, circular linked list)
• Implementing basic operations on linked lists (insertion, deletion, traversal)
• Analyzing the time and space complexity of linked list operations

Stacks and Queues

• Understanding the concepts of stacks and queues
• Implementing stack and queue operations using arrays and linked lists
• Exploring stack and queue applications and use cases

Trees

• Understanding binary trees and their properties
• Implementing binary tree traversal algorithms (pre-order, in-order, post-order)
• Exploring binary search trees and their operations (insertion, deletion, search)

Heap and Priority Queue

• Understanding the concepts of heap and priority queue
• Implementing heap operations (insertion, deletion, heapify)
• Exploring priority queue applications and use cases

Hashing and Hash Tables

• Understanding the concept of hashing and hash functions
• Implementing hash tables for efficient data storage and retrieval
• Analyzing collision resolution techniques (chaining, open addressing)

Graphs

• Understanding graph representations (adjacency matrix, adjacency list)
• Implementing graph traversal algorithms (breadth-first search, depth-first search)
• Exploring graph algorithms (shortest path, minimum spanning tree)

Advanced Data Structures

• Exploring advanced data structures like AVL trees, red-black trees, and B-trees
• Understanding their properties and applications
• Analyzing the time and space complexity of advanced data structure operations

Algorithms and Data Structure Analysis

• Analyzing time and space complexity of various data structure operations
• Understanding algorithm analysis techniques (big O notation, asymptotic analysis)
• Evaluating the efficiency and performance of data structures

Recursion

• Understanding the concept of recursion and its application in data structures
• Implementing recursive algorithms for solving problems
• Analyzing recursive algorithm complexity and potential pitfalls

Dynamic Programming

• Understanding the concept of dynamic programming and its application in data structures
• Solving problems using dynamic programming techniques
• Analyzing the time and space complexity of dynamic programming algorithms

Advanced Topics

• Exploring advanced data structure topics like trie, disjoint sets, segment trees
• Understanding their applications and use cases
• Analyzing the time and space complexity of advanced data structures

Design and Analysis of Data Structures

• Applying principles of design and analysis in developing efficient data structures
• Evaluating trade-offs in data structure design decisions
• Solving real-world problems using appropriate data structures