AlgorithmsDynamic ProgrammingGreedy AlgorithmDivide And Conquer AlgorithmsRandomized AlgorithmSorting AlgorithmGraphsData StructureHash TableSpanning TreeNp-Completeness
48,881 人已註冊
提供方
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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.
應用的學習項目
Learners will practice and master the fundamentals of algorithms through several types of assessments. Every week, there is a multiple choice quiz to test your understanding of the most important concepts. There are also weekly programming assignments, where you implement one of the algorithms covered in lecture in a programming language of your choosing. Each course concludes with a multiple-choice final exam.
學生職業成果
62%
完成此 專項課程 後開始了新的職業。
26%
加薪或升職。
學生職業成果
62%
完成此 專項課程 後開始了新的職業。
26%
加薪或升職。
100% 在線課程
立即開始，按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
中級
需要一些相關領域經驗。需要一些相關經驗。
完成時間大約為4 個月
建議 8 小時/週
英語（English）
字幕：英語（English）
專項課程的運作方式
加入課程
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實踐項目
每個專項課程都包括實踐項目。您需要成功完成這個（些）項目才能完成專項課程並獲得證書。如果專項課程中包括單獨的實踐項目課程，則需要在開始之前完成其他所有課程。
獲得證書
在結束每門課程並完成實踐項目之後，您會獲得一個證書，您可以向您的潛在雇主展示該證書並在您的職業社交網絡中分享。
此專項課程包含 4 門課程
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
3,506 個評分
The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).
Graph Search, Shortest Paths, and Data Structures
1,493 個評分
The primary topics in this part of the specialization are: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social network analysis).
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
944 個評分
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).
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
584 個評分
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).
提供方
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.
審閱
4.8
來自算法的熱門評論
由 CV 提供Jun 10, 2017
A really exciting and challenging course. Loved the way the instructor explained everything with so much detail and precision. Definitely looking forward to the next course in the specialization.
由 AS 提供Aug 22, 2018
This is the most challenging course in this specialization. Assignments as well as test questions require good amount of thinking.\n\nOne of the best courses I did on Coursera.
由 ML 提供Nov 12, 2019
very interesting course in Algorithms Specialization.\n\nIt is sufficient to arouse interest in studying advance algorithm.\n\nThank you for your teaching, Professor Tim.
由 SA 提供Mar 15, 2020
A really well-crafted specialization. Has something for everyone from a beginner to an advanced Computer Science student.
由 SS 提供Jan 23, 2017
very good course! but I think this specialization focus on mathematical analysis, we need to practice more
由 YZ 提供Aug 12, 2018
Really happy to finish this specialization and I will still study algorithms in the future.
由 YW 提供May 13, 2019
This course is harder than the previous two in the specialization but equally fun.
由 SJ 提供Jul 23, 2017
This is the most challenging course of all the courses in the specialization
常見問題
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可以！点击您感兴趣的课程卡开始注册即可。注册并完成课程后，您可以获得可共享的证书，或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某专项课程的一部分，系统会自动为您订阅完整的专项课程。访问您的学生面板，跟踪您的进度。
有助学金吗？
我可以免费学习课程吗？
此课程是 100% 在线学习吗？是否需要现场参加课程？
此课程完全在线学习，无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。
完成专项课程需要多长时间？
The Specialization has four four-week courses, for a total of sixteen weeks.
What background knowledge is necessary?
Learners should know how to program in at least one programming language (like C, Java, or Python); some familiarity with proofs, including proofs by induction and by contradiction; and some discrete probability, like how to compute the probability that a poker hand is a full house. At Stanford, a version of this course is taken by sophomore, junior, and senior-level computer science majors.
Do I need to take the courses in a specific order?
For best results, the courses should be taken in order.
完成专项课程后我会获得大学学分吗？
No.
What will I be able to do upon completing the Specialization?
Having taken your programming and thinking skills to the next level, you will be well positioned to ace your technical interviews, pursue serious software engineering, and study advanced topics in algorithms.
還有其他問題嗎？請訪問 學生幫助中心。
