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

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).

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What's inside

Syllabus

Week 1

The Bellman-Ford algorithm; all-pairs shortest paths.

Week 2

NP-complete problems and exact algorithms for them.

Week 3

Approximation algorithms for NP-complete problems.

Week 4

Local search algorithms for NP-complete problems; the wider world of algorithms.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Covers shortest paths, NP-completeness, and algorithms for hard problems

Provides strategies for dealing with computationally intractable problems

Taught by Tim Roughgarden, an expert in algorithm design and complexity theory

Assumes prior knowledge of algorithms and data structures

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Reviews summary

Highly rated course

Learners say that this highly rated course stands out for its engaging assignments and outstanding instructor.

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Shortest Paths Revisited, NP-Complete Problems and What To Do About Them with these activities:

Read 'Introduction to Algorithms' by Cormen, Leiserson, and Rivest

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Expand your foundational knowledge in algorithms by reading this comprehensive textbook, which covers essential concepts and techniques.

View Introduction to Algorithms, fourth edition on Amazon

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Read the chapters relevant to the course topics.
Take notes and highlight important sections.
Review and reinforce key concepts regularly.

Review the basics of graph theory

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Refresh your knowledge of graph theory concepts such as nodes, edges, and paths to better understand the algorithms covered in this course.

Browse courses on Graph Theory

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Review the definitions and properties of graphs.
Practice drawing and representing graphs.
Solve problems involving graph traversal techniques.

Follow tutorials on local search algorithms

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Enhance your understanding of local search algorithms by following guided tutorials and exploring different implementation techniques.

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Find tutorials on local search algorithms.
Follow the tutorials and implement the algorithms.
Experiment with different parameters and scenarios.

Six other activities

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Solve practice problems on shortest paths algorithms

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Reinforce your understanding of shortest paths algorithms by solving a variety of practice problems covering different scenarios and complexities.

Browse courses on Shortest Path Algorithms

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Implement the Bellman-Ford algorithm.
Apply Floyd-Warshall algorithm to find all-pairs shortest paths.
Solve problems using Johnson's algorithm.

Discuss strategies for coping with computationally intractable problems

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Exchange ideas and learn from peers about different strategies for dealing with problems that are difficult to solve exactly.

Browse courses on Approximation Algorithms

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Share your understanding of approximation algorithms.
Discuss the benefits and limitations of local search algorithms.
Brainstorm real-world scenarios where these strategies can be applied.

Write a blog post on the applications of NP-completeness

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Solidify your knowledge of NP-completeness by explaining its significance and real-world applications in a written blog post.

Browse courses on NP-Completeness

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Research and understand the concept of NP-completeness.
Identify real-world problems that are NP-complete.
Write a blog post discussing these applications and their implications.

Develop a heuristic algorithm for an NP-complete problem

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Apply your understanding of NP-completeness and heuristic techniques by designing and implementing a heuristic algorithm for a real-world problem.

Browse courses on NP-Complete Problems

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Identify an NP-complete problem.
Research and understand existing heuristic algorithms.
Design and implement your own heuristic algorithm.
Test and evaluate the performance of your algorithm.

Contribute to an open-source project related to graph algorithms

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Gain practical experience and contribute to the community by participating in an open-source project focused on graph algorithms.

Browse courses on Graph Algorithms

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Find an open-source project related to graph algorithms.
Review the project's codebase and documentation.
Identify areas where you can contribute.
Submit a pull request with your contributions.

Develop a web application that utilizes a shortest path algorithm

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Apply your knowledge of shortest path algorithms by building a real-world web application that incorporates these techniques.

Browse courses on Shortest Path Algorithms

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Design the architecture and user interface of the application.
Implement the shortest path algorithm in the backend.
Develop the frontend to interact with the backend.
Test and deploy the application.

Career center

Learners who complete Shortest Paths Revisited, NP-Complete Problems and What To Do About Them will develop knowledge and skills that may be useful to these careers:

Algorithm Engineer

An Algorithm Engineer designs and develops algorithms to solve computational problems. This course is highly relevant to an Algorithm Engineer because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics are essential for designing and developing efficient and effective algorithms.

See salaries and explore the career path for Algorithm Engineer

Computer Scientist

A Computer Scientist studies the theory and design of computers and software. This course may be useful for a Computer Scientist because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help a Computer Scientist develop the skills needed to design and implement efficient and effective computer systems and software.

See salaries and explore the career path for Computer Scientist

Information Technology Manager

An Information Technology Manager plans, implements, and manages the information technology systems of an organization. This course may be useful for an Information Technology Manager because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help an Information Technology Manager develop the skills needed to design and implement efficient and effective information technology systems.

See salaries and explore the career path for Information Technology Manager

Software Developer

A Software Developer designs, develops, and maintains software applications. This course may be useful for a Software Developer because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help a Software Developer develop the skills needed to design and develop efficient and effective software applications.

See salaries and explore the career path for Software Developer

Systems Analyst

A Systems Analyst designs and implements computer systems. This course may be useful for a Systems Analyst because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help a Systems Analyst develop the skills needed to design and implement efficient and effective computer systems.

See salaries and explore the career path for Systems Analyst

Software Engineer

A Software Engineer designs, develops, and maintains software applications. This course may be useful for a Software Engineer because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help a Software Engineer develop the skills needed to design and develop efficient and effective software applications.

See salaries and explore the career path for Software Engineer

Data Analyst

A Data Analyst analyzes data to identify trends and patterns. This course may be useful for a Data Analyst because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help a Data Analyst develop the skills needed to analyze data and identify trends and patterns.

See salaries and explore the career path for Data Analyst

Data Scientist

A Data Scientist uses data to solve problems and make predictions. This course may be useful for a Data Scientist because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help a Data Scientist develop the skills needed to analyze data and solve complex problems.

See salaries and explore the career path for Data Scientist

Quantitative Analyst

A Quantitative Analyst uses mathematical and statistical models to analyze data and make predictions. This course may be useful for a Quantitative Analyst because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help a Quantitative Analyst develop the skills needed to analyze data and make predictions.

See salaries and explore the career path for Quantitative Analyst

Operations Manager

An Operations Manager plans, organizes, and manages the operations of an organization. This course may be useful for an Operations Manager because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help an Operations Manager develop the skills needed to plan, organize, and manage the operations of an organization effectively.

See salaries and explore the career path for Operations Manager

Project Manager

A Project Manager plans, organizes, and manages projects. This course may be useful for a Project Manager because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help a Project Manager develop the skills needed to plan, organize, and manage projects effectively.

See salaries and explore the career path for Project Manager

Business Analyst

A Business Analyst helps organizations improve their performance by analyzing data and making recommendations. This course may be useful for a Business Analyst because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help a Business Analyst develop the skills needed to analyze data and make recommendations to improve the performance of organizations.

See salaries and explore the career path for Business Analyst

Management Consultant

A Management Consultant helps organizations improve their performance by providing advice and recommendations. This course may be useful for a Management Consultant because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help a Management Consultant develop the skills needed to analyze data and make recommendations to improve the performance of organizations.

See salaries and explore the career path for Management Consultant

Business Intelligence Analyst

A Business Intelligence Analyst uses data to help organizations make better decisions. This course may be useful for a Business Intelligence Analyst because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help a Business Intelligence Analyst develop the skills needed to analyze data and help organizations make better decisions.

See salaries and explore the career path for Business Intelligence Analyst

Operations Research Analyst

An Operations Research Analyst applies analytical methods to help organizations improve their efficiency and make better decisions. This course may be useful for an Operations Research Analyst because it covers topics such as shortest paths, NP-completeness, and local search algorithms. These topics can help an Operations Research Analyst develop the skills needed to solve complex problems and improve the efficiency of organizations.

See salaries and explore the career path for Operations Research Analyst

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Shortest Paths Revisited, NP-Complete Problems and What To Do About Them.

Introduction to Algorithms, fourth edition

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Classic textbook on algorithms and valuable reference for anyone interested in learning more about the subject. It covers a wide range of topics, including shortest paths, NP-completeness, and approximation algorithms.

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

Three deals to help you save

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Highly rated course

Activities

Career center

Reading list

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