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.
Algorithms 專項課程
Learn To Think Like A Computer Scientist。 Master the fundamentals of the design and analysis of algorithms.
本專項課程介紹
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.
製作方：
4 courses
按照建議的順序或選擇您自己的順序。
項目
旨在幫助您實踐和應用所學到的技能。
證書
在您的簡歷和領英中展示您的新技能。
項目概覽
課程
- Intermediate Specialization.
- Some related experience required.
第 1 門課程
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
- 課程學習時間
- 4 weeks of study, 4-8 hours/week
- 字幕
- English
課程概述
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, contra您可以選擇只參加本課程。 了解更多。
第 2 門課程
Graph Search, Shortest Paths, and Data Structures
- 課程學習時間
- 4 weeks of study, 4-8 hours/week
- 字幕
- English
課程概述
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您可以選擇只參加本課程。 了解更多。
第 3 門課程
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
- 課程學習時間
- 4 weeks of study, 4-8 hours/week
- 字幕
- English
課程概述
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, op您可以選擇只參加本課程。 了解更多。
第 4 門課程
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
- 課程學習時間
- 4 weeks of study, 4-8 hours/week
- 字幕
- English
課程概述
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 (analys您可以選擇只參加本課程。 了解更多。
製作方
Tim Roughgarden
Professor
FAQs
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