- Data Structures and Algorithms
Introduction to Data Structures and Algorithms- Importance and Applications
- Basic Definitions
- Efficiency Analysis (Time and Space Complexity)
Fundamentals of Programming- Variables and Data Types
- Control Structures (if, else, switch)
- Loops (for, while, do-while)
Array and Strings- Arrays
- Strings
- Operations and Manipulations
Linked Lists- Singly Linked Lists
- Doubly Linked Lists
- Circular Linked Lists
- Operations and Implementations
Stacks and Queues- Stack Operations
- Queue Operations
- Applications
Trees- Binary Trees
- Binary Search Trees
- AVL Trees
- Heaps
- Tree Traversals (In-order, Pre-order, Post-order)
Graphs- Graph Representation (Adjacency Matrix, Adjacency List)
- Depth-First Search (DFS)
- Breadth-First Search (BFS)
- Shortest Path Algorithms (Dijkstra's, Bellman-Ford)
- Minimum Spanning Tree (Prim's, Kruskal's)
Hashing- Hash Functions
- Hash Tables
- Collision Resolution
Sorting and Searching- Sorting Algorithms (Bubble, Selection, Insertion, Merge, Quick, Heap)
- Searching Algorithms (Linear Search, Binary Search)
Dynamic Programming- Concept and Applications
- Memoization and Tabulation
Divide and Conquer- Concept and Applications
- Merge Sort, Quick Sort
Greedy Algorithms- Concept and Applications
- Huffman Coding
Advanced Topics- Trie
- Segment Tree
- Disjoint Set (Union-Find)
Algorithmic Paradigms- Backtracking
- Bit Manipulation
Complexity Classes- P, NP, NP-Complete
Case Studies and Real-world Applications- Application of DSA in Software Development
Interview Preparation- Commonly Asked DSA Questions
- Problem-solving Strategies
Best Practices and Coding Standards- Code Optimization
- Readable and Maintainable Code
- Importance and Applications
- Basic Definitions
- Time and Space Complexity
- Learn about basic data structures: arrays, stacks, and queues.
- Implement and practice using stacks and queues.
- Solve problems involving these data structures.
- Singly and doubly linked lists.
- Operations on linked lists.
- Bubble sort, selection sort, insertion sort.
- Quick sort, merge sort & Heap sort.
- Linear search and binary search.
- Practice implementing and applying searching algorithms.
- Binary trees, binary search trees (BST), AVL Tree, Heap.
- Tree traversal algorithms (in-order, pre-order, post-order).
- Basics of graphs: representation and traversal.
- Depth-First Search (DFS) and Breadth-First Search (BFS).
- AVL trees, Red-Black trees.
- Advanced graph algorithms (Dijkstra's, Bellman-Ford, etc.).
- Understanding the concept of overlapping sub-problems and optimal substructure.
- Start with basic DP problems.
- Progress to more complex problems as you become comfortable.
- Hashing, heaps, tries.
- Applications and use cases.
- Advanced sorting algorithms (e.g., heap sort).
- String matching algorithms.
- Go back to challenging problems and concepts.
- Mock interviews and real-world problem-solving.
HAPPY LEARNING !!
DEVELOPED WITH ❤️ BY SNEH KR