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MSC Semester I - DESIGN AND ANALYSIS OF ALGORITHMS (DS)

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MSC Semester I - DESIGN AND ANALYSIS OF ALGORITHMS (DS)

MSC Semester I - DESIGN AND ANALYSIS OF ALGORITHMS

updated on icon Updated on Jun, 2025

language icon Language - English

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category icon Development ,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: 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, Traveling

Salesperson Problem.

UNIT-III

Basic Traversal and Search Techniques: Techniques for Binary Trees, Techniques for

Graphs, Connected Components and Spanning Trees, Biconnected Components, and DFS.

Backtracking: General Method, 8-Queens Problem, Sum of Subsets, Graph Coloring

Hamiltonian Cycles, Knapsack Problem.

Branch-and-Bound: General Method, 0/1 Knapsack Problem, Traveling 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.


MSC Semester I - DESIGN AND ANALYSIS OF ALGORITHMS (DS)

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction to Data Structures and Algorithms

22 Lectures
  • play icon Recursion Introduction 06:40 06:40
  • play icon 15.3.1. Algorithm run time- Introduction 1 05:28 05:28
  • play icon Introduction of DSA 04:39 04:39
  • play icon Why Recursion? 02:31 02:31
  • play icon 15.3.1. Algorithm run time- Introduction 2 04:31 04:31
  • play icon Introduction to DSA- Part 2 04:26 04:26
  • play icon Format used and Internal working of Recursion 02:48 02:48
  • play icon Time complexity 04:40 04:40
  • play icon Introduction to DSA- Part 3 04:17 04:17
  • play icon Examples of Recursion 04:20 04:20
  • play icon Example of Implementation - Part 1 02:11 02:11
  • play icon Introduction to DSA- Part 4 01:57 01:57
  • play icon Recursion vs Iteration 02:25 02:25
  • play icon Example of Implementation - Part 2 02:41 02:41
  • play icon Introduction to DSA- Part 5 02:47 02:47
  • play icon Advantage and Disadvantages of Recursion 03:52 03:52
  • play icon Example of Implementation - Part 3 02:25 02:25
  • play icon Introduction to DSA- Part 6 01:57 01:57
  • play icon Recursion Implementation- Part 1 03:57 03:57
  • play icon Python Implementation 07:10 07:10
  • play icon Recursion Implementation- Part 2 05:50 05:50
  • play icon Search in Recursion Implementation 18:31 18:31

Algorithm Runtimes

7 Lectures
Tutorialspoint

Linear Datastructures

45 Lectures
Tutorialspoint

Non - Linear Data structures

46 Lectures
Tutorialspoint

Concept of Binary Heaps

10 Lectures
Tutorialspoint

Hashing and Sorting

26 Lectures
Tutorialspoint

Advance Data structure

30 Lectures
Tutorialspoint

Instructor Details

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