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Shortest Paths & NP-Complete Problems
This course is part of Algorithms Specialization.
Course Cost
Free course
Intermediate
Skill Level
12 Hours
Self-paced lessons
This intermediate-level course explores advanced algorithms focusing on three key areas: shortest path algorithms, NP-completeness theory, and strategies for handling computationally intractable problems. You'll master fundamental algorithms like Bellman-Ford, Floyd-Warshall, and Johnson for solving shortest path problems in various graph scenarios. The course then delves into NP-completeness and its implications for algorithm design, equipping you with a theoretical framework to understand computational complexity. Finally, you'll explore practical approaches for dealing with intractable problems, including approximation algorithms, heuristics, local search techniques, and dynamic programming. Throughout the course, you'll apply these concepts through programming assignments and problem sets, gaining hands-on experience that reinforces theoretical understanding.
47,949 Enrolled
English
What you'll learn
Implement and analyze the Bellman-Ford algorithm for single-source shortest paths
Master all-pairs shortest path algorithms like Floyd-Warshall and Johnson's algorithm
Understand NP-completeness and its implications for algorithm design
Design exact algorithms for NP-complete problems like Vertex Cover and Traveling Salesman
Develop approximation algorithms and heuristics for NP-complete problems
Implement and analyze local search algorithms for optimization problems
Apply dynamic programming techniques to computationally challenging problems
Skills you'll gain
This course includes:
7.75 Hours PreRecorded video
9 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This course, part of the Algorithms Specialization, covers three main topics: shortest paths algorithms, NP-completeness theory, and strategies for handling computationally intractable problems. The shortest paths section explores Bellman-Ford, Floyd-Warshall, and Johnson's algorithms for single-source and all-pairs problems. The NP-completeness modules provide a theoretical framework for understanding problem complexity and its implications for algorithm design. The final sections focus on practical approaches to intractable problems, including approximation algorithms, heuristics, and local search techniques. Throughout the course, students apply concepts through programming assignments and problem sets, developing both theoretical understanding and practical implementation skills.
Week 1
Module 1 · 4 Hours to complete
Week 2
Module 2 · 3 Hours to complete
Week 3
Module 3 · 1 Hours to complete
Week 4
Module 4 · 4 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Algorithms Specialization
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Faculties
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Frequently asked Questions
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