Data Structure Courses - Unisoft Technologies Nagpur
Data Structure with C Programming
Data Structures is a fundamental subject in modern Computer Science. Every programmer and developer must be well versed with it. This course helps you understand the design, implementation and analysis of Data Structures through C.
Data Structure with C++ Programming
Data Structures and Algorithms are the building blocks of programming complex solutions. Using DSA, you can solve complex problems without any hustle. It tells you to choose algorithms based on the program’s needs. C++ helps you in several factors such as memory management and time complexity instructions in an efficient manner and DSA with C++ is a plus point.
Course Content:
2. Algorithm Analysis [3 hours]
- Time Complexity Analysis (Big O notation).
- Space Complexity Analysis.
- Asymptotic Analysis of Algorithms.
- Recursion and Recursive Algorithms.
- Practical
3. Linear Data Structure [9 hours]
- Stacks : Operations and Applications [theory/practical].
- Queue : Operations and Applications [theory/practical].
- Circular Queue : Operations and Applications [theory/practical].
- Deque : Operations and Applications [theory/practical].
- Practical.
4. Linked Lists [7 hours]
- Operation – Creation, Insertion, Deletion [theory/practical].
- Doubly Linked Lists [theory/practical].
- Circular Linked Lists [theory/practical].
- Practical
5. Sorting Algorithm [5 hours]
- Bubble Sort [1 hour theory/practical].
- Selection Sort [1 hour theory/practical].
- Insertion Sort [1 hour theory/practical].
- Merge Sort [1 hour theory/practical].
- Quick Sort [1 hour theory/practical].
- Practical
6. Searching Algorithm [2 hours]
- Linear Search [1 hour theory/practical].
- Binary Search [1 hour theory/practical].
- Practical
7. Trees [11 hours]
- Binary Trees [theory/practical].
- Operation : Insert, Delete.
- Traversal : Preorder, Inorder, Postorder.
- Binary Search Trees [theory/practical].
- Operation : Insert, Delete.
- Traversal : Preorder, Inorder, Postorder.
- AVL Trees [theory/practical].
- Heaps [4 hours]
- Min heap.
- Max heap.
- Practical
8. Graphs I : Representation an Traversal [4 hours]
- Representation : Adancency Matrix, Adancency List.
- Traversal : Breadth-First Search (BFS), Depth-First Search (DFS).
9. Graphs II : Basic Algorithms [4 hours]
- Minimum Spanning Tree Algorithms : Kruskal's algorithm for minimum spanning tree,Prim's algorithm for minimum spanning tree.
- Shortest Path Algorithms : Dijkstra's algorithm for shortest paths, Bellman-Ford algorithm for shortest paths.
10. Tables [3 hours]
- Hashing Techniques.
11. Sets [3 hours]
- Representation.
- Operation : Union and Find.
12. String Algorithms [7 hours]
- String manipulation and processing.
- Pattern matching algorithms : Naive, Rabin-Karp, Knuth-Morris-Pratt (KMP)
13. Program Development [2 hours]
- Program Specification.
- Pre and Post Condition.
- Program Documentation.