关于此 专项课程
100% 在线课程

100% 在线课程

立即开始,按照自己的计划学习。
灵活的计划

灵活的计划

设置并保持灵活的截止日期。
中级

中级

Basic knowledge of at least one programming language: C++, Java, Python, C, C#, Javascript, Haskell, Kotlin, Ruby, Rust, Scala. Basic knowledge of discrete mathematics: proof by induction, proof by contradiction.

完成时间(小时)

完成时间大约为6 个月

建议 7 小时/周
可选语言

英语(English)

字幕:英语(English), 西班牙语(Spanish)...

您将获得的技能

DebuggingSoftware TestingAlgorithmsData StructureComputer Programming
100% 在线课程

100% 在线课程

立即开始,按照自己的计划学习。
灵活的计划

灵活的计划

设置并保持灵活的截止日期。
中级

中级

Basic knowledge of at least one programming language: C++, Java, Python, C, C#, Javascript, Haskell, Kotlin, Ruby, Rust, Scala. Basic knowledge of discrete mathematics: proof by induction, proof by contradiction.

完成时间(小时)

完成时间大约为6 个月

建议 7 小时/周
可选语言

英语(English)

字幕:英语(English), 西班牙语(Spanish)...

专项课程 的运作方式

加入课程

Coursera 专项课程是帮助您掌握一门技能的一系列课程。若要开始学习,请直接注册专项课程,或预览专项课程并选择您要首先开始学习的课程。当您订阅专项课程的部分课程时,您将自动订阅整个专项课程。您可以只完成一门课程,您可以随时暂停学习或结束订阅。访问您的学生面板,跟踪您的课程注册情况和进度。

实践项目

每个专项课程都包括实践项目。您需要成功完成这个(些)项目才能完成专项课程并获得证书。如果专项课程中包括单独的实践项目课程,则需要在开始之前完成其他所有课程。

获得证书

在结束每门课程并完成实践项目之后,您会获得一个证书,您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。

how it works

此专项课程包含 6 门课程

课程1

Algorithmic Toolbox

4.7
3,784 个评分
836 个审阅
The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second)....
课程2

Data Structures

4.7
1,638 个评分
282 个审阅
A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures. A few examples of questions that we are going to cover in this class are the following: 1. What is a good strategy of resizing a dynamic array? 2. How priority queues are implemented in C++, Java, and Python? 3. How to implement a hash table so that the amortized running time of all operations is O(1) on average? 4. What are good strategies to keep a binary tree balanced? You will also learn how services like Dropbox manage to upload some large files instantly and to save a lot of storage space!...
课程3

Algorithms on Graphs

4.7
890 个评分
155 个审阅
If you have ever used a navigation service to find optimal route and estimate time to destination, you've used algorithms on graphs. Graphs arise in various real-world situations as there are road networks, computer networks and, most recently, social networks! If you're looking for the fastest time to get to work, cheapest way to connect set of computers into a network or efficient algorithm to automatically find communities and opinion leaders in Facebook, you're going to work with graphs and algorithms on graphs. In this course, you will first learn what a graph is and what are some of the most important properties. Then you'll learn several ways to traverse graphs and how you can do useful things while traversing the graph in some order. We will then talk about shortest paths algorithms — from the basic ones to those which open door for 1000000 times faster algorithms used in Google Maps and other navigational services. You will use these algorithms if you choose to work on our Fast Shortest Routes industrial capstone project. We will finish with minimum spanning trees which are used to plan road, telephone and computer networks and also find applications in clustering and approximate algorithms....
课程4

Algorithms on Strings

4.5
481 个评分
98 个审阅
World and internet is full of textual information. We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. To make sense of all that information and make search efficient, search engines use many string algorithms. Moreover, the emerging field of personalized medicine uses many search algorithms to find disease-causing mutations in the human genome....

讲师

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Daniel M Kane

Assistant Professor
Department of Computer Science and Engineering / Department of Mathematics
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Neil Rhodes

Adjunct Faculty
Computer Science and Engineering
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Pavel Pevzner

Professor
Department of Computer Science and Engineering
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Michael Levin

Lecturer
Computer Science
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Alexander S. Kulikov

Visiting Professor
Department of Computer Science and Engineering

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关于 University of California San Diego

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory....

关于 National Research University Higher School of Economics

National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communications, IT, mathematics, engineering, and more. Learn more on www.hse.ru...

常见问题

  • 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。

  • 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。

  • 此专项课程不提供大学学分,但部分大学可能会选择接受专项课程证书作为学分。查看您的合作院校了解详情。

  • You will be able to apply the right algorithms and data structures in your day-to-day work and write programs that work in some cases many orders of magnitude faster. You'll be able to solve algorithmic problems like those used in the technical interviews at Google, Facebook, Microsoft, Yandex, etc. If you do data science, you'll be able to significantly increase the speed of some of your experiments. You'll also have a completed Capstone either in Bioinformatics or in the Shortest Paths in Road Networks and Social Networks that you can demonstrate to potential employers.

  • 1. Basic knowledge of at least one programming language: C++, Java, Python, C, C#, Javascript, Haskell, Kotlin, Ruby, Rust, Scala.

    We expect you to be able to implement programs that: 1) read data from the standard input (in most cases, the input is a sequence of integers); 2) compute the result (in most cases, a few loops are enough for this); 3) print the result to the standard output. For each programming challenge in this course, we provide starter solutions in C++, Java, and Python. The best way to check whether your programming skills are enough to go through problems in this specialization is to solve two problems from the first week. If you are able to pass them (after reading our tutorials), then you will definitely be able to pass the course.

    2. Basic knowledge of discrete mathematics: proof by induction, proof by contradiction.

    Knowledge of discrete mathematics is necessary for analyzing algorithms (proving correctness, estimating running time) and for algorithmic thinking in general. If you want to refresh your discrete mathematics skills, we encourage you to go through our partner specialization — Introduction to Discrete Mathematics for Computer Science (https://www.coursera.org/specializations/discrete-mathematics). It teaches the basics of discrete mathematics in try-this-before-we-explain-everything approach: you will be solving many interactive puzzles that were carefully designed to allow you to invent many of the important ideas and concepts yoursel

  • We believe that learning the theory behind algorithms (like in most Algorithms 101 courses taught at 1000s universities) is important but not sufficient for a professional computer scientist today. This specialization combines the theory of algorithms with many programming challenges. In contrast with many Algorithms 101 courses, you will implement over 100 algorithmic problems in the programming language of your choice. And you will see yourself that the best way to understand an algorithm is to implement it!

  • Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 6-8 months.

  • Each course in the Specialization is offered on a regular schedule, with sessions starting about once per month. If you don't complete a course on the first try, you can easily transfer to the next session, and your completed work and grades will carry over.

  • We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.

  • The lectures in this specialization will be self-contained. Most lectures will be based on the bestselling textbook "Algorithms" co-authored by Sanjoy Dasgupta from University of California at San Diego as well as Christos Papadimitriou and Umesh Vazirani from University of California at Berkeley. In addition to UCSD and Berkeley, the textbook has been adopted in over 100 top universities and is available on Internet.

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