The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
教學大綱 - 您將從這門課程中學到什麼
週
1Week 1
Two motivating applications; selected review; introduction to greedy algorithms; a scheduling application; Prim's MST algorithm.
16 個視頻 （總計 160 分鐘）, 4 個閱讀材料, 2 個測驗
16 個視頻
Application: Sequence Alignment8分鐘
Introduction to Greedy Algorithms12分鐘
Application: Optimal Caching10分鐘
Problem Definition5分鐘
A Greedy Algorithm12分鐘
Correctness Proof - Part I6分鐘
Correctness Proof - Part II4分鐘
Handling Ties [Advanced - Optional]7分鐘
MST Problem Definition11分鐘
Prim's MST Algorithm7分鐘
Correctness Proof I15分鐘
Correctness Proof II8分鐘
Proof of Cut Property [Advanced - Optional]11分鐘
Fast Implementation I14分鐘
Fast Implementation II9分鐘
4 個閱讀材料
Week 1 Overview10分鐘
Overview, Resources, and Policies10分鐘
Lecture slides10分鐘
Optional Theory Problems (Week 1)10分鐘
2 個練習
Problem Set #110分鐘
Programming Assignment #16分鐘
週
2Week 2
Kruskal's MST algorithm and applications to clustering; advanced union-find (optional).
16 個視頻 （總計 188 分鐘）, 2 個閱讀材料, 2 個測驗
16 個視頻
Correctness of Kruskal's Algorithm9分鐘
Implementing Kruskal's Algorithm via Union-Find I9分鐘
Implementing Kruskal's Algorithm via Union-Find II13分鐘
MSTs: State-of-the-Art and Open Questions [Advanced - Optional]9分鐘
Application to Clustering11分鐘
Correctness of Clustering Algorithm9分鐘
Lazy Unions [Advanced - Optional]10分鐘
Union-by-Rank [Advanced - Optional]12分鐘
Analysis of Union-by-Rank [Advanced - Optional]14分鐘
Path Compression [Advanced - Optional]14分鐘
Path Compression: The Hopcroft-Ullman Analysis I [Advanced - Optional]9分鐘
Path Compression: The Hopcroft-Ullman Analysis II [Advanced - Optional]11分鐘
The Ackermann Function [Advanced - Optional]16分鐘
Path Compression: Tarjan's Analysis I [Advanced - Optional]14分鐘
Path Compression: Tarjan's Analysis II [Advanced - Optional]13分鐘
2 個閱讀材料
Week 2 Overview10分鐘
Optional Theory Problems (Week 2)10分鐘
2 個練習
Problem Set #210分鐘
Programming Assignment #24分鐘
週
3Week 3
Huffman codes; introduction to dynamic programming.
11 個視頻 （總計 105 分鐘）, 1 個閱讀材料, 2 個測驗
11 個視頻
Problem Definition10分鐘
A Greedy Algorithm16分鐘
A More Complex Example4分鐘
Correctness Proof I10分鐘
Correctness Proof II12分鐘
Introduction: Weighted Independent Sets in Path Graphs7分鐘
WIS in Path Graphs: Optimal Substructure9分鐘
WIS in Path Graphs: A Linear-Time Algorithm9分鐘
WIS in Path Graphs: A Reconstruction Algorithm6分鐘
Principles of Dynamic Programming7分鐘
1 個閱讀材料
Week 3 Overview10分鐘
2 個練習
Problem Set #310分鐘
Programming Assignment #36分鐘
週
4Week 4
Advanced dynamic programming: the knapsack problem, sequence alignment, and optimal binary search trees.
10 個視頻 （總計 107 分鐘）, 3 個閱讀材料, 3 個測驗
10 個視頻
A Dynamic Programming Algorithm9分鐘
Example [Review - Optional]12分鐘
Optimal Substructure13分鐘
A Dynamic Programming Algorithm12分鐘
Problem Definition12分鐘
Optimal Substructure9分鐘
Proof of Optimal Substructure6分鐘
A Dynamic Programming Algorithm I9分鐘
A Dynamic Programming Algorithm II9分鐘
3 個閱讀材料
Week 4 Overview10分鐘
Optional Theory Problems (Week 4)10分鐘
Info and FAQ for final exam10分鐘
3 個練習
Problem Set #410分鐘
Programming Assignment #44分鐘
Final Exam20分鐘
4.8
71 個審閱38%
完成這些課程後已開始新的職業生涯
45%
通過此課程獲得實實在在的工作福利
14%
加薪或升職
熱門審閱
創建者 JP•Oct 20th 2018
Great learning experience!!!\n\nI love dynamic p the most.\n\nAssignment 4 is so challenging that it takes me a week to finish the program and debug it!!!
創建者 AJ•Feb 9th 2017
I love how clear the videos (and notes) are and re-watching them really helped a lot! I wish there was more discussion on the forms though!
講師
Tim Roughgarden
ProfessorComputer Science
關於 斯坦福大学
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.
關於 算法 專項課程
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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