# Stanford University - Shortest Paths Revisited, NP-Complete Problems and What To Do About Them

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## Shortest Paths Revisited, NP-Complete Problems and What To Do About Them at Coursera Overview

 Duration 14 hours Start from Start Now Total fee Free Mode of learning Online Difficulty level Intermediate Official Website Explore Free Course Credential Certificate

## Shortest Paths Revisited, NP-Complete Problems and What To Do About Them at Coursera Highlights

• Shareable Certificate Earn a Certificate upon completion
• 100% online Start instantly and learn at your own schedule.
• Course 4 of 4 in the Algorithms Specialization
• Intermediate Level
• Approx. 14 hours to complete
• English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish

## Shortest Paths Revisited, NP-Complete Problems and What To Do About Them at Coursera Course details

Skills you will learn
• The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).

## Shortest Paths Revisited, NP-Complete Problems and What To Do About Them at Coursera Curriculum

Week 1

Single-Source Shortest Paths, Revisted

Optimal Substructure

The Basic Algorithm I

The Basic Algorithm II

Detecting Negative Cycles

A Space Optimization

Internet Routing I [Optional]

Internet Routing II [Optional]

Problem Definition

Optimal Substructure

The Floyd-Warshall Algorithm

A Reweighting Technique

Johnson's Algorithm I

Johnson's Algorithm II

Week 1 Overview

Overview, Resources, and Policies

Lecture Slides

Optional Theory Problems (Week 1)

Problem Set #1

Programming Assignment #1

Week 2

Polynomial-Time Solvable Problems

Reductions and Completeness

Definition and Interpretation of NP-Completeness I

Definition and Interpretation of NP-Completeness II

The P vs. NP Question

Algorithmic Approaches to NP-Complete Problems

The Vertex Cover Problem

Smarter Search for Vertex Cover I

Smarter Search for Vertex Cover II

The Traveling Salesman Problem

A Dynamic Programming Algorithm for TSP

Week 2 Overview

Optional Theory Problems (Week 2)

Problem Set #2

Programming Assignment #2

Week 3

A Greedy Knapsack Heuristic

Analysis of a Greedy Knapsack Heuristic I

Analysis of a Greedy Knapsack Heuristic II

A Dynamic Programming Heuristic for Knapsack

Knapsack via Dynamic Programming, Revisited

Ananysis of Dynamic Programming Heuristic

Week 3 Overview

Problem Set #3

Programming Assignment #3

Week 4

The Maximum Cut Problem I

The Maximum Cut Problem II

Principles of Local Search I

Principles of Local Search II

The 2-SAT Problem

Random Walks on a Line

Stable Matching [Optional]

Matchings, Flows, and Braess's Paradox [Optional]

Linear Programming and Beyond [Optional]

Epilogue

Week 4 Overview

Optional Theory Problems (Week 4)

Info and FAQ for final exam

Problem Set #4

Programming Assignment #4

Final Exam

## Important Dates

May 25, 2024
Course Commencement Date

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