About this Course
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다음 전문 분야의 1개 강좌 중 1번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

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

완료하는 데 약 28시간 필요

권장: 4 weeks of study, 5-10 hours/week...

영어

자막: 영어

귀하가 습득할 기술

Binary Search TreePriority QueueHash TableStack (Abstract Data Type)List

다음 전문 분야의 1개 강좌 중 1번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

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

완료하는 데 약 28시간 필요

권장: 4 weeks of study, 5-10 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 4시간 필요

Basic Data Structures

In this module, you will learn about the basic data structures used throughout the rest of this course. We start this module by looking in detail at the fundamental building blocks: arrays and linked lists. From there, we build up two important data structures: stacks and queues. Next, we look at trees: examples of how they’re used in Computer Science, how they’re implemented, and the various ways they can be traversed. Once you’ve completed this module, you will be able to implement any of these data structures, as well as have a solid understanding of the costs of the operations, as well as the tradeoffs involved in using each data structure.

...
7 videos (Total 60 min), 7 readings, 2 quizzes
7개의 동영상
Singly-Linked Lists9m
Doubly-Linked Lists4m
Stacks10m
Queues7m
Trees11m
Tree Traversal10m
7개의 읽기 자료
Welcome10m
Slides and External References10m
Slides and External References10m
Slides and External References10m
Available Programming Languages10m
FAQ on Programming Assignments10m
Acknowledgements10m
1개 연습문제
Basic Data Structures10m
2
완료하는 데 1시간 필요

Dynamic Arrays and Amortized Analysis

In this module, we discuss Dynamic Arrays: a way of using arrays when it is unknown ahead-of-time how many elements will be needed. Here, we also discuss amortized analysis: a method of determining the amortized cost of an operation over a sequence of operations. Amortized analysis is very often used to analyse performance of algorithms when the straightforward analysis produces unsatisfactory results, but amortized analysis helps to show that the algorithm is actually efficient. It is used both for Dynamic Arrays analysis and will also be used in the end of this course to analyze Splay trees.

...
5 videos (Total 31 min), 1 reading, 1 quiz
5개의 동영상
Amortized Analysis: Aggregate Method5m
Amortized Analysis: Banker's Method6m
Amortized Analysis: Physicist's Method7m
Amortized Analysis: Summary2m
1개의 읽기 자료
Slides and External References10m
1개 연습문제
Dynamic Arrays and Amortized Analysis8m
3
완료하는 데 6시간 필요

Priority Queues and Disjoint Sets

We start this module by considering priority queues which are used to efficiently schedule jobs, either in the context of a computer operating system or in real life, to sort huge files, which is the most important building block for any Big Data processing algorithm, and to efficiently compute shortest paths in graphs, which is a topic we will cover in our next course. For this reason, priority queues have built-in implementations in many programming languages, including C++, Java, and Python. We will see that these implementations are based on a beautiful idea of storing a complete binary tree in an array that allows to implement all priority queue methods in just few lines of code. We will then switch to disjoint sets data structure that is used, for example, in dynamic graph connectivity and image processing. We will see again how simple and natural ideas lead to an implementation that is both easy to code and very efficient. By completing this module, you will be able to implement both these data structures efficiently from scratch.

...
15 videos (Total 129 min), 6 readings, 4 quizzes
15개의 동영상
Naive Implementations of Priority Queues5m
Binary Trees1m
Basic Operations12m
Complete Binary Trees9m
Pseudocode8m
Heap Sort10m
Building a Heap10m
Final Remarks4m
Overview7m
Naive Implementations10m
Trees for Disjoint Sets7m
Union by Rank9m
Path Compression6m
Analysis (Optional)18m
6개의 읽기 자료
Slides10m
Tree Height Remark10m
Slides and External References10m
Slides and External References10m
Slides and External References10m
Slides and External References10m
3개 연습문제
Priority Queues: Quiz12m
Quiz: Disjoint Sets8m
Priority Queues and Disjoint Sets6m
4
완료하는 데 6시간 필요

Hash Tables

In this module you will learn about very powerful and widely used technique called hashing. Its applications include implementation of programming languages, file systems, pattern search, distributed key-value storage and many more. You will learn how to implement data structures to store and modify sets of objects and mappings from one type of objects to another one. You will see that naive implementations either consume huge amount of memory or are slow, and then you will learn to implement hash tables that use linear memory and work in O(1) on average! In the end, you will learn how hash functions are used in modern disrtibuted systems and how they are used to optimize storage of services like Dropbox, Google Drive and Yandex Disk!

...
22 videos (Total 170 min), 4 readings, 3 quizzes
22개의 동영상
Analysing Service Access Logs7m
Direct Addressing7m
List-based Mapping8m
Hash Functions3m
Chaining Scheme6m
Chaining Implementation and Analysis5m
Hash Tables6m
Phone Book Problem4m
Phone Book Problem - Continued6m
Universal Family9m
Hashing Integers9m
Proof: Upper Bound for Chain Length (Optional)8m
Proof: Universal Family for Integers (Optional)11m
Hashing Strings9m
Hashing Strings - Cardinality Fix7m
Search Pattern in Text7m
Rabin-Karp's Algorithm9m
Optimization: Precomputation9m
Optimization: Implementation and Analysis5m
Instant Uploads and Storage Optimization in Dropbox10m
Distributed Hash Tables12m
4개의 읽기 자료
Slides and External References10m
Slides and External References10m
Slides and External References10m
Slides and External References10m
2개 연습문제
Hash Tables and Hash Functions8m
Hashing6m
4.7
347개의 리뷰Chevron Right

38%

이 강좌를 수료한 후 새로운 경력 시작하기

41%

이 강좌를 통해 확실한 경력상 이점 얻기

14%

급여 인상 또는 승진하기

데이터 구조의 최상위 리뷰

대학: DGMay 24th 2016

I like this course very much! Rope is the cleverest task I have ever done! Of course, I hope in future I will work on even more difficult problems, but this is pretty good already for me as a student!

대학: TTApr 6th 2018

Data Structures was really interesting over all, also assignments are quite challenging. It's important to consult the external references & discussion forums if you want to get the best of it.

강사

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Alexander S. Kulikov

Visiting Professor
Department of Computer Science and Engineering
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Michael Levin

Lecturer
Computer Science
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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

캘리포니아 샌디에고 대학교 정보

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....

국립 연구 고등 경제 대학 정보

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 communicamathematics, engineering, and more. Learn more on www.hse.ru...

데이터 구조 및 알고리즘 전문 분야 정보

This specialization is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems and will implement about 100 algorithmic coding problems in a programming language of your choice. No other online course in Algorithms even comes close to offering you a wealth of programming challenges that you may face at your next job interview. To prepare you, we invested over 3000 hours into designing our challenges as an alternative to multiple choice questions that you usually find in MOOCs. Sorry, we do not believe in multiple choice questions when it comes to learning algorithms...or anything else in computer science! For each algorithm you develop and implement, we designed multiple tests to check its correctness and running time — you will have to debug your programs without even knowing what these tests are! It may sound difficult, but we believe it is the only way to truly understand how the algorithms work and to master the art of programming. The specialization contains two real-world projects: Big Networks and Genome Assembly. You will analyze both road networks and social networks and will learn how to compute the shortest route between New York and San Francisco (1000 times faster than the standard shortest path algorithms!) Afterwards, you will learn how to assemble genomes from millions of short fragments of DNA and how assembly algorithms fuel recent developments in personalized medicine....
데이터 구조 및 알고리즘

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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