MSC Semester I - DESIGN AND ANALYSIS OF ALGORITHMS (DS)
MSC Semester I - DESIGN AND ANALYSIS OF ALGORITHMS
Updated on Feb, 2026
Language - English
Programming,Data Science,Data Analysis
Lectures -186
Resources -10
Duration -17.5 hours
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Course Description
UNIT – I: INTRODUCTION TO ALGORITHMS
Algorithm Specification; Performance Analysis; Randomized Algorithms.
Elementary Data Structures: Stacks and Queues; Trees; Dictionaries; Priority Queues; Sets and Disjoint Set Union; Graphs.
Divide and Conquer: Binary Search; Finding the Maximum and Minimum; Merge Sort; Quick Sort; Selection Sort; Strassen's Matrix Multiplication; Convex Hull.
UNIT – II: GREEDY METHOD AND DYNAMIC PROGRAMMING
Greedy Method: Knapsack Problem; Job Sequencing with Deadlines; Minimum-Cost Spanning Trees (Kruskal's & Prim's); Single Source Shortest Paths (Dijkstra's).
Dynamic Programming: General Method; Multistage Graphs; All-Pairs Shortest Paths; Single-Source Shortest Paths; Optimal Binary Search Trees; 0/1 Knapsack; Travelling Salesperson Problem.
UNIT – III: TRAVERSAL TECHNIQUES, BACKTRACKING AND BRANCH-AND-BOUND
Basic Traversal and Search Techniques: Techniques for Binary Trees; Techniques for Graphs; Connected Components and Spanning Trees; Biconnected Components; DFS.
Backtracking: General Method; 8-Queens Problem; Sum of Subsets; Graph Colouring; Hamiltonian Cycles; Knapsack Problem.
Branch-and-Bound: General Method; 0/1 Knapsack Problem; Travelling Salesperson Problem.
UNIT – IV: NP-HARD AND NP-COMPLETE PROBLEMS
Basic Concepts; Cook's Theorem; NP-Hard Graph Problems; NP-Hard Scheduling Problems; NP-Hard Code Generation; Some Simplified NP-Hard Problems.
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction to Data Structures and Algorithms
22 Lectures
-
Recursion Introduction
06:40
06:40
-
15.3.1. Algorithm run time- Introduction 1
05:28
05:28
-
Introduction of DSA
04:39
04:39
-
Why Recursion?
02:31
02:31
-
15.3.1. Algorithm run time- Introduction 2
04:31
04:31
-
Introduction to DSA- Part 2
04:26
04:26
-
Format used and Internal working of Recursion
02:48
02:48
-
Time complexity
04:40
04:40
-
Introduction to DSA- Part 3
04:17
04:17
-
Examples of Recursion
04:20
04:20
-
Example of Implementation - Part 1
02:11
02:11
-
Introduction to DSA- Part 4
01:57
01:57
-
Recursion vs Iteration
02:25
02:25
-
Example of Implementation - Part 2
02:41
02:41
-
Introduction to DSA- Part 5
02:47
02:47
-
Advantage and Disadvantages of Recursion
03:52
03:52
-
Example of Implementation - Part 3
02:25
02:25
-
Introduction to DSA- Part 6
01:57
01:57
-
Recursion Implementation- Part 1
03:57
03:57
-
Python Implementation
07:10
07:10
-
Recursion Implementation- Part 2
05:50
05:50
-
Search in Recursion Implementation
18:31
18:31
Algorithm Runtimes
7 Lectures
Linear Datastructures
45 Lectures
Non - Linear Data structures
46 Lectures
Concept of Binary Heaps
10 Lectures
Hashing and Sorting
26 Lectures
Advance Data structure
30 Lectures
Instructor Details
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