Об этом курсе
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Рецензии: 285
Специализация

Курс 2 из 6 в программе

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Промежуточный уровень

Промежуточный уровень

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

Часов на завершение

Прибл. 29 часа на выполнение

Предполагаемая нагрузка: 4 weeks of study, 5-10 hours/week...
Доступные языки

Английский

Субтитры: Английский

Приобретаемые навыки

Binary Search TreePriority QueueHash TableStack (Abstract Data Type)List
Специализация

Курс 2 из 6 в программе

100% онлайн

100% онлайн

Начните сейчас и учитесь по собственному графику.
Гибкие сроки

Гибкие сроки

Назначьте сроки сдачи в соответствии со своим графиком.
Промежуточный уровень

Промежуточный уровень

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

Часов на завершение

Прибл. 29 часа на выполнение

Предполагаемая нагрузка: 4 weeks of study, 5-10 hours/week...
Доступные языки

Английский

Субтитры: Английский

Программа курса: что вы изучите

Неделя
1
Часов на завершение
4 ч. на завершение

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....
Reading
7 видео ((всего 60 мин.)), 7 материалов для самостоятельного изучения, 2 тестов
Video7 видео
Arrays7мин
Singly-Linked Lists9мин
Doubly-Linked Lists4мин
Stacks10мин
Queues7мин
Trees11мин
Tree Traversal10мин
Reading7 материала для самостоятельного изучения
Welcome10мин
Slides and External References10мин
Slides and External References10мин
Slides and External References10мин
Available Programming Languages10мин
FAQ on Programming Assignments10мин
Acknowledgements10мин
Quiz1 практическое упражнение
Basic Data Structures10мин
Неделя
2
Часов на завершение
1 ч. на завершение

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....
Reading
5 видео ((всего 31 мин.)), 1 материал для самостоятельного изучения, 1 тест
Video5 видео
Amortized Analysis: Aggregate Method5мин
Amortized Analysis: Banker's Method6мин
Amortized Analysis: Physicist's Method7мин
Amortized Analysis: Summary2мин
Reading1 материал для самостоятельного изучения
Slides and External References10мин
Quiz1 практическое упражнение
Dynamic Arrays and Amortized Analysis8мин
Неделя
3
Часов на завершение
6 ч. на завершение

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....
Reading
15 видео ((всего 129 мин.)), 6 материалов для самостоятельного изучения, 4 тестов
Video15 видео
Naive Implementations of Priority Queues5мин
Binary Trees1мин
Basic Operations12мин
Complete Binary Trees9мин
Pseudocode8мин
Heap Sort10мин
Building a Heap10мин
Final Remarks4мин
Overview7мин
Naive Implementations10мин
Trees for Disjoint Sets7мин
Union by Rank9мин
Path Compression6мин
Analysis (Optional)18мин
Reading6 материала для самостоятельного изучения
Slides10мин
Tree Height Remark10мин
Slides and External References10мин
Slides and External References10мин
Slides and External References10мин
Slides and External References10мин
Quiz3 практического упражнения
Priority Queues: Quiz12мин
Quiz: Disjoint Sets8мин
Priority Queues and Disjoint Sets6мин
Неделя
4
Часов на завершение
6 ч. на завершение

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!...
Reading
22 видео ((всего 170 мин.)), 4 материалов для самостоятельного изучения, 3 тестов
Video22 видео
Analysing Service Access Logs7мин
Direct Addressing7мин
List-based Mapping8мин
Hash Functions3мин
Chaining Scheme6мин
Chaining Implementation and Analysis5мин
Hash Tables6мин
Phone Book Problem4мин
Phone Book Problem - Continued6мин
Universal Family9мин
Hashing Integers9мин
Proof: Upper Bound for Chain Length (Optional)8мин
Proof: Universal Family for Integers (Optional)11мин
Hashing Strings9мин
Hashing Strings - Cardinality Fix7мин
Search Pattern in Text7мин
Rabin-Karp's Algorithm9мин
Optimization: Precomputation9мин
Optimization: Implementation and Analysis5мин
Instant Uploads and Storage Optimization in Dropbox10мин
Distributed Hash Tables12мин
Reading4 материала для самостоятельного изучения
Slides and External References10мин
Slides and External References10мин
Slides and External References10мин
Slides and External References10мин
Quiz2 практического упражнения
Hash Tables and Hash Functions8мин
Hashing6мин
4.7
Рецензии: 285Chevron Right
Карьерные преимущества

20%

получил значимые преимущества в карьере благодаря этому курсу
Продвижение по карьерной лестнице

14%

стал больше зарабатывать или получил повышение

Лучшие рецензии

автор: 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!

автор: 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.

Преподавателя

Avatar

Alexander S. Kulikov

Visiting Professor
Department of Computer Science and Engineering
Avatar

Michael Levin

Lecturer
Computer Science
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Daniel M Kane

Assistant Professor
Department of Computer Science and Engineering / Department of Mathematics
Avatar

Neil Rhodes

Adjunct Faculty
Computer Science and Engineering

О 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....

О 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...

О специализации ''Data Structures and Algorithms'

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....
Data Structures and Algorithms

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