- Algorithm Analysis.
- Linear Data Structures.
- Linked List.
- Stack.
- Queues.
In computer science, a data structure is a particular way of organizing and storing data in a computer so that it can be accessed and modified efficiently. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data.
- This Course is ideal for any or student and advanced users who wish to maximize their productivity using Data Structures.
- Concept.
- Data type, Data object, ADT.
- Need of Data Structure.
- Types of Data Structure.
- Algorithm – definition, characteristics.
- Space complexity, time complexity.
- Asymptotic notation (Big O, Omega Ω).
- Introduction to Arrays - array representation.
- Sorting algorithms with efficiency.
- bubble sort, Insertion sort, Merge sort, Quick Sort.
- Introduction to List.
- Implementation of List – static & dynamic representation.
- Types of Linked List.
- Operations on List.
- Applications of Linked List – polynomial manipulation.
- Generalized linked list – concept & representation.
- Introduction.
- Representation-static & dynamic.
- Operations.
- Application - infix to postfix & prefix, postfix evaluation.
- Recursion using implicit stack.
- Concept of Multiple stacks.
- Introduction.
- Representation -static & dynamic.
- Operations.
- Circuler queue, DeQue, priority queues.
- Concept of Multiple Queues.
- Concept & Terminologies.
- Binary tree, binary search tree.
- Representation – static & dynamic.
- Operations on BST – create. Insert, delete, traversals (preorder, inorder, postorder), counting leaf, non-leaf & total nodes.
- Application - Heap sort Height balance tree- AVL trees- Rotations.
- Passing an array element to a function.
- Rules of using an Array.
- Concept & terminologies.
- Graph Representation.
- Traversals – BFS & DFS.
- Applications – AOV network – topological sort.
- AOE network – critical path.
- Shortest path with implementation.
