Our Java Data Structures Course covers the most commonly used data structures and algorithms,
providing you with a comprehensive toolkit for efficient coding.
1. Introduction to Data Structures
Understanding the importance of data structures and
algorithms
Big O notation and complexity analysis
Arrays and Linked Lists: Implementation, operations, and use
cases
2. Stacks and Queues
Stack implementation using arrays and linked lists
Queue and Deque: Operations and
applications
Practical use cases of stacks and queues in software
development
3. Trees and Graphs
Learn to store, manage, and retrieve data efficiently.
Introduction to Trees: Binary Tree, Binary
Search Tree (BST)
Tree traversal algorithms (Inorder, Preorder,
Postorder)
AVL Trees and balanced tree concepts
Graphs: Representation using adjacency
matrix and adjacency list
Graph traversal algorithms: BFS and
DFS
4. Hashing and HashMaps
Understanding hashing and its applications
Implementing hash tables and hash maps in Java
Collision resolution techniques (Chaining, Open
Addressing)
Real-world applications of hash maps
5. Sorting and Searching Algorithms
Bubble Sort, Insertion Sort, Selection Sort
Quick Sort, Merge Sort, and their optimizations
Binary Search and its application in data
structures
Sorting algorithms comparison and use cases
6. Advanced Data Structures
Heaps and Priority Queues: Implementation
and applications
Trees:Efficient data retrieval with prefix
trees
Disjoint Set Union (DSU) and Union-Find algorithms
Segment Trees and Fenwick Trees for range queries
