When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
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).
The Bellman-Ford algorithm; all-pairs shortest paths.
What's included
14 videos4 readings2 assignments
Show info about module content
14 videos•Total 151 minutes
Single-Source Shortest Paths, Revisted•11 minutes
Optimal Substructure•11 minutes
The Basic Algorithm I•9 minutes
The Basic Algorithm II•11 minutes
Detecting Negative Cycles•9 minutes
A Space Optimization•13 minutes
Internet Routing I [Optional]•11 minutes
Internet Routing II [Optional]•7 minutes
Problem Definition•7 minutes
Optimal Substructure•12 minutes
The Floyd-Warshall Algorithm•13 minutes
A Reweighting Technique•14 minutes
Johnson's Algorithm I•11 minutes
Johnson's Algorithm II•12 minutes
4 readings•Total 40 minutes
Week 1 Overview•10 minutes
Overview, Resources, and Policies•10 minutes
Lecture Slides•10 minutes
Optional Theory Problems (Week 1)•10 minutes
2 assignments•Total 60 minutes
Problem Set #1•30 minutes
Programming Assignment #1•30 minutes
Week 2
Module 2•3 hours to complete
Module details
NP-complete problems and exact algorithms for them.
What's included
11 videos2 readings2 assignments
Show info about module content
11 videos•Total 122 minutes
Polynomial-Time Solvable Problems•14 minutes
Reductions and Completeness•14 minutes
Definition and Interpretation of NP-Completeness I•11 minutes
Definition and Interpretation of NP-Completeness II•8 minutes
The P vs. NP Question•9 minutes
Algorithmic Approaches to NP-Complete Problems•13 minutes
The Vertex Cover Problem•9 minutes
Smarter Search for Vertex Cover I•10 minutes
Smarter Search for Vertex Cover II•8 minutes
The Traveling Salesman Problem•15 minutes
A Dynamic Programming Algorithm for TSP•12 minutes
2 readings•Total 20 minutes
Week 2 Overview•10 minutes
Optional Theory Problems (Week 2)•10 minutes
2 assignments•Total 60 minutes
Problem Set #2•30 minutes
Programming Assignment #2•30 minutes
Week 3
Module 3•2 hours to complete
Module details
Approximation algorithms for NP-complete problems.
What's included
6 videos1 reading2 assignments
Show info about module content
6 videos•Total 68 minutes
A Greedy Knapsack Heuristic•14 minutes
Analysis of a Greedy Knapsack Heuristic I•7 minutes
Analysis of a Greedy Knapsack Heuristic II•10 minutes
A Dynamic Programming Heuristic for Knapsack•12 minutes
Knapsack via Dynamic Programming, Revisited•10 minutes
Ananysis of Dynamic Programming Heuristic•15 minutes
1 reading•Total 10 minutes
Week 3 Overview•10 minutes
2 assignments•Total 32 minutes
Problem Set #3•30 minutes
Programming Assignment #3•2 minutes
Week 4
Module 4•4 hours to complete
Module details
Local search algorithms for NP-complete problems; the wider world of algorithms.
What's included
11 videos3 readings3 assignments
Show info about module content
11 videos•Total 124 minutes
The Maximum Cut Problem I•8 minutes
The Maximum Cut Problem II•9 minutes
Principles of Local Search I•9 minutes
Principles of Local Search II•10 minutes
The 2-SAT Problem•15 minutes
Random Walks on a Line•16 minutes
Analysis of Papadimitriou's Algorithm•15 minutes
Stable Matching [Optional]•15 minutes
Matchings, Flows, and Braess's Paradox [Optional]•14 minutes
Linear Programming and Beyond [Optional]•11 minutes
Epilogue•1 minute
3 readings•Total 30 minutes
Week 4 Overview•10 minutes
Optional Theory Problems (Week 4)•10 minutes
Info and FAQ for final exam•10 minutes
3 assignments•Total 90 minutes
Problem Set #4•30 minutes
Programming Assignment #4•30 minutes
Final Exam•30 minutes
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The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
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B
BG
5·
Reviewed on Jul 6, 2018
Excellent course! Bravo to the teacher for the commitment provided in this course. Kind regards.
A
AS
5·
Reviewed on Aug 22, 2018
This is the most challenging course in this specialization. Assignments as well as test questions require good amount of thinking. One of the best courses I did on Coursera.
T
TL
5·
Reviewed on Mar 4, 2018
Thanks a lot. It is time consuming, need a lot of thinking and practising to finish the homework. And it is worth taking. After this, we can go deep into cs.
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To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.