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).
提供：
アルゴリズム の専門講座スタンフォード大学（Stanford University）このコースについて
41,401 最近の表示
受講生の就業成果
62%
コース終了後に新しいキャリアをスタートした
50%
コースが具体的なキャリアアップにつながった
12%
昇給や昇進につながった
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における4の4コース
柔軟性のある期限
スケジュールに従って期限をリセットします。
中級レベル
約11時間で修了
英語
字幕：英語
習得するスキル
Data StructureAlgorithmsNp-CompletenessDynamic Programming
受講生の就業成果
62%
コース終了後に新しいキャリアをスタートした
50%
コースが具体的なキャリアアップにつながった
12%
昇給や昇進につながった
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における4の4コース
柔軟性のある期限
スケジュールに従って期限をリセットします。
中級レベル
約11時間で修了
英語
字幕：英語
提供：
スタンフォード大学（Stanford University）
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.
シラバス - 本コースの学習内容
3時間で修了
Week 1
The Bellman-Ford algorithm; all-pairs shortest paths.
3時間で修了
14件のビデオ （合計151分）, 4 readings, 2 quizzes
14件のビデオ
Optimal Substructure10 分
The Basic Algorithm I8 分
The Basic Algorithm II10 分
Detecting Negative Cycles9 分
A Space Optimization12 分
Internet Routing I [Optional]11 分
Internet Routing II [Optional]6 分
Problem Definition7 分
Optimal Substructure12 分
The Floyd-Warshall Algorithm13 分
A Reweighting Technique14 分
Johnson's Algorithm I11 分
Johnson's Algorithm II11 分
4件の学習用教材
Week 1 Overview10 分
Overview, Resources, and Policies10 分
Lecture Slides10 分
Optional Theory Problems (Week 1)10 分
2の練習問題
Problem Set #110 分
Programming Assignment #12 分
3時間で修了
Week 2
NP-complete problems and exact algorithms for them.
3時間で修了
11件のビデオ （合計122分）, 2 readings, 2 quizzes
11件のビデオ
Reductions and Completeness13 分
Definition and Interpretation of NP-Completeness I10 分
Definition and Interpretation of NP-Completeness II7 分
The P vs. NP Question9 分
Algorithmic Approaches to NP-Complete Problems12 分
The Vertex Cover Problem8 分
Smarter Search for Vertex Cover I9 分
Smarter Search for Vertex Cover II7 分
The Traveling Salesman Problem14 分
A Dynamic Programming Algorithm for TSP12 分
2件の学習用教材
Week 2 Overview10 分
Optional Theory Problems (Week 2)10 分
2の練習問題
Problem Set #210 分
Programming Assignment #22 分
2時間で修了
Week 3
Approximation algorithms for NP-complete problems.
2時間で修了
6件のビデオ （合計68分）, 1 reading, 2 quizzes
6件のビデオ
Analysis of a Greedy Knapsack Heuristic I7 分
Analysis of a Greedy Knapsack Heuristic II9 分
A Dynamic Programming Heuristic for Knapsack11 分
Knapsack via Dynamic Programming, Revisited10 分
Ananysis of Dynamic Programming Heuristic15 分
1件の学習用教材
Week 3 Overview10 分
2の練習問題
Problem Set #310 分
Programming Assignment #32 分
3時間で修了
Week 4
Local search algorithms for NP-complete problems; the wider world of algorithms.
3時間で修了
11件のビデオ （合計124分）, 3 readings, 3 quizzes
11件のビデオ
The Maximum Cut Problem II9 分
Principles of Local Search I8 分
Principles of Local Search II10 分
The 2-SAT Problem14 分
Random Walks on a Line16 分
Analysis of Papadimitriou's Algorithm14 分
Stable Matching [Optional]15 分
Matchings, Flows, and Braess's Paradox [Optional]13 分
Linear Programming and Beyond [Optional]11 分
Epilogue1 分
3件の学習用教材
Week 4 Overview10 分
Optional Theory Problems (Week 4)10 分
Info and FAQ for final exam10 分
3の練習問題
Problem Set #410 分
Programming Assignment #42 分
Final Exam20 分
レビュー
SHORTEST PATHS REVISITED, NP-COMPLETE PROBLEMS AND WHAT TO DO ABOUT THEM からの人気レビュー
AAにより2017年2月27日
This challenging course improves understanding of algorithms and is intellectually stimulating. I learnt the theory behind algorithms and how they are applied to solve real world problems.
ASにより2018年8月22日
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.
MLにより2019年11月12日
very interesting course in Algorithms Specialization. It is sufficient to arouse interest in studying advance algorithm.\n\nThank you for your teaching, Professor Tim.
JEにより2019年12月27日
I am very confident in the skills I learned. I have read some books on algorithms but this course makes the application so clear regardless of your programing language.
アルゴリズム専門講座について
Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists.
About the instructor: Tim Roughgarden has been a professor in the Computer Science Department at Stanford University since 2004. He has taught and published extensively on the subject of algorithms and their applications.
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Is financial aid available?
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