Your roadmap · आपका रोडमैप
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Admission & first meetingप्रवेश और पहली मुलाकातEnquire at your nearest NDSS centre, meet the teacher, fix the batch time and get your study material.
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Part 1 of the syllabusपाठ्यक्रम भाग 1Unit-wise coaching with notes and doubt classes.
Unit 1: Introduction, Arrays and Linked ListsUnit 2: Stacks, Queues, Searching, Sorting and HashingUnit 3: Trees
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Part 2 of the syllabusपाठ्यक्रम भाग 2Unit-wise coaching with notes and doubt classes.
Unit 4: GraphsUnit 5: Algorithm Design Techniques
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Unit tests & assignmentsयूनिट टेस्टRegular tests in the university / board pattern.
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Semester 2 exam (university / board)विश्वविद्यालय / बोर्ड परीक्षाPrevious papers and full revision before the exam.
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Online tests & resultऑनलाइन टेस्ट और रिज़ल्टTake the tests online; your marks and result show in your student login and at the centre.
Syllabus · पाठ्यक्रम
1 subject · 5 chapters · 30 topics
01Unit 1: Introduction, Arrays and Linked Lists
6 topics+
- Data structures and abstract data types
- Algorithm complexity: time and space
- Asymptotic notations: big-O, Omega, Theta
- Arrays: row-major and column-major address calculation
- Singly, doubly and circular linked lists
- Polynomial representation using linked lists
02Unit 2: Stacks, Queues, Searching, Sorting and Hashing
6 topics+
- Stack operations and applications
- Infix to postfix conversion and postfix evaluation
- Queues, circular queues, deques and priority queues
- Linear and binary search
- Insertion, selection, bubble, quick, merge and heap sort
- Hashing: hash functions and collision resolution
03Unit 3: Trees
6 topics+
- Binary tree terminology and representation
- Tree traversals: preorder, inorder, postorder
- Binary search tree operations
- AVL trees and rotations
- Heaps and B-trees
- Huffman coding
04Unit 4: Graphs
6 topics+
- Graph terminology and representations
- Breadth-first and depth-first search
- Minimum spanning tree: Prim's and Kruskal's algorithms
- Single-source shortest path: Dijkstra and Bellman-Ford
- All-pairs shortest path: Floyd-Warshall
- Topological sort
05Unit 5: Algorithm Design Techniques
6 topics+
- Divide and conquer and the master theorem
- Greedy method: fractional knapsack, activity selection
- Dynamic programming: 0/1 knapsack, LCS, matrix chain multiplication
- Backtracking: N-Queens, subset sum
- Branch and bound
- P, NP, NP-complete and NP-hard classes
About this course
You will be able to
- Analyse algorithms using asymptotic notation and recurrence relations
- Implement arrays, linked lists, stacks and queues and use them in applications
- Compare searching, sorting and hashing techniques by complexity
- Build and traverse binary trees, BSTs, AVL trees, heaps and B-trees
- Apply BFS, DFS, minimum spanning tree and shortest-path algorithms to graphs
- Solve problems using divide and conquer, greedy, dynamic programming and backtracking
Who it is for
- MCA students of Semester 2 (AKTU, Lucknow)
- Students preparing for coding interviews, GATE and UGC-NET
What you need
- Programming in C (pointers and structures)
- Basic discrete mathematics
Online tests & result
Practice and unit tests online; marks and result show in your student login and at the centre.
Student login →
Questions
Which syllabus does this Data Structures & Analysis of Algorithms course follow?
It follows the AKTU (Lucknow) MCA syllabus for Semester 2. If your own university's syllabus differs, the centre follows your university's syllabus and unit order.
Will I write programs too?
Yes. All major structures and algorithms are implemented in the Data Structures & Analysis of Algorithms Lab.
How are students tested at the centre?
Unit-wise MCQ tests, numerical / problem practice, previous AKTU question papers and a final mock paper before the semester exam.
