Explore common techniques and challenges with arrays and strings, fundamental data structures in programming.
2. Sorting and Searching Arrays
Explore various sorting algorithms to organize data efficiently.
3. Linked Lists
Understand and manipulate singly linked lists, a basic data structure for storing sequences.
4. Stacks & Queues
Dive into stack and queue structures to handle data where order of operations is crucial.
5. Hash Tables
Explore hash tables to efficiently store and retrieve data based on keys.
6. Binary Trees I: Fundamentals
Master the basics of binary trees with a focus on their construction, node management, and essential traversal techniques like DFS and BFS.
7. Binary Trees II: Common Applications
Explore advanced binary tree operations such as height calculation, balance checking, LCA determination, and path optimization for deep tree manipulation.
8. Binary Search Trees (BST)
Deep dive into Binary Search Trees for efficient data sorting and retrieval.
9. Binary Heaps
Understand binary heaps to implement priority queues and sort data efficiently.
10. Tries
Explore Tries for efficient information retrieval and auto-completion features.
11. Graphs
Understand and manipulate graphs, a fundamental data structure for modeling relationships.
12. Dynamic Programming
Master dynamic programming, key techniques for solving complex problems that involve breaking them down into simpler subproblems.
13. Greedy Algorithms
Learn to solve problems using greedy algorithms, which make the locally optimal choice at each step.
14. Bit Manipulation
Delve into bit manipulation techniques to handle data at the machine-level.