About this Course
최근 조회 367,386

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

완료하는 데 약 34시간 필요

권장: 5 weeks of study, 4-8 hours/week...

영어

자막: 영어, 스페인어

배울 내용

  • Check

    Essential algorithmic techniques

  • Check

    Design efficient algorithms

  • Check

    Practice solving algorithmic interview problems

  • Check

    Implement efficient and reliable solutions

귀하가 습득할 기술

Dynamic ProgrammingDebuggingSoftware TestingAlgorithmsComputer Programming

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

완료하는 데 약 34시간 필요

권장: 5 weeks of study, 4-8 hours/week...

영어

자막: 영어, 스페인어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 5시간 필요

Programming Challenges

Welcome to the first module of Data Structures and Algorithms! Here we will provide an overview of where algorithms and data structures are used (hint: everywhere) and walk you through a few sample programming challenges. The programming challenges represent an important (and often the most difficult!) part of this specialization because the only way to fully understand an algorithm is to implement it. Writing correct and efficient programs is hard; please don’t be surprised if they don’t work as you planned—our first programs did not work either! We will help you on your journey through the specialization by showing how to implement your first programming challenges. We will also introduce testing techniques that will help increase your chances of passing assignments on your first attempt. In case your program does not work as intended, we will show how to fix it, even if you don’t yet know which test your implementation is failing on.

...
6 videos (Total 48 min), 6 readings, 3 quizzes
6개의 동영상
Solving the Sum of Two Digits Programming Challenge (screencast)6m
Solving the Maximum Pairwise Product Programming Challenge: Improving the Naive Solution, Testing, Debugging13m
Stress Test - Implementation8m
Stress Test - Find the Test and Debug7m
Stress Test - More Testing, Submit and Pass!8m
6개의 읽기 자료
Companion MOOCBook10m
What background knowledge is necessary?10m
Optional Videos and Screencasts10m
Maximum Pairwise Product Programming Challenge10m
Using PyCharm to solve programming challenges10m
Acknowledgements2m
1개 연습문제
Solving Programming Challenges20m
2
완료하는 데 5시간 필요

Algorithmic Warm-up

In this module you will learn that programs based on efficient algorithms can solve the same problem billions of times faster than programs based on naïve algorithms. You will learn how to estimate the running time and memory of an algorithm without even implementing it. Armed with this knowledge, you will be able to compare various algorithms, select the most efficient ones, and finally implement them as our programming challenges!

...
12 videos (Total 77 min), 3 readings, 4 quizzes
12개의 동영상
Coming Up3m
Problem Overview3m
Naive Algorithm5m
Efficient Algorithm3m
Problem Overview and Naive Algorithm4m
Efficient Algorithm5m
Computing Runtimes10m
Asymptotic Notation6m
Big-O Notation6m
Using Big-O10m
Course Overview10m
3개의 읽기 자료
Resources2m
Resources2m
Resources2m
3개 연습문제
Logarithms10m
Big-O10m
Growth rate10m
3
완료하는 데 4시간 필요

Greedy Algorithms

In this module you will learn about seemingly naïve yet powerful class of algorithms called greedy algorithms. After you will learn the key idea behind the greedy algorithms, you may feel that they represent the algorithmic Swiss army knife that can be applied to solve nearly all programming challenges in this course. But be warned: with a few exceptions that we will cover, this intuitive idea rarely works in practice! For this reason, it is important to prove that a greedy algorithm always produces an optimal solution before using this algorithm. In the end of this module, we will test your intuition and taste for greedy algorithms by offering several programming challenges.

...
10 videos (Total 56 min), 1 reading, 3 quizzes
10개의 동영상
Car Fueling7m
Car Fueling - Implementation and Analysis9m
Main Ingredients of Greedy Algorithms2m
Celebration Party Problem6m
Efficient Algorithm for Grouping Children5m
Analysis and Implementation of the Efficient Algorithm5m
Long Hike6m
Fractional Knapsack - Implementation, Analysis and Optimization6m
Review of Greedy Algorithms2m
1개의 읽기 자료
Resources2m
2개 연습문제
Greedy Algorithms10m
Fractional Knapsack10m
4
완료하는 데 7시간 필요

Divide-and-Conquer

In this module you will learn about a powerful algorithmic technique called Divide and Conquer. Based on this technique, you will see how to search huge databases millions of times faster than using naïve linear search. You will even learn that the standard way to multiply numbers (that you learned in the grade school) is far from the being the fastest! We will then apply the divide-and-conquer technique to design two efficient algorithms (merge sort and quick sort) for sorting huge lists, a problem that finds many applications in practice. Finally, we will show that these two algorithms are optimal, that is, no algorithm can sort faster!

...
20 videos (Total 157 min), 5 readings, 6 quizzes
20개의 동영상
Linear Search7m
Binary Search7m
Binary Search Runtime8m
Problem Overview and Naïve Solution6m
Naïve Divide and Conquer Algorithm7m
Faster Divide and Conquer Algorithm6m
What is the Master Theorem?4m
Proof of the Master Theorem9m
Problem Overview2m
Selection Sort8m
Merge Sort10m
Lower Bound for Comparison Based Sorting12m
Non-Comparison Based Sorting Algorithms7m
Overview2m
Algorithm9m
Random Pivot13m
Running Time Analysis (optional)15m
Equal Elements6m
Final Remarks8m
5개의 읽기 자료
Resources10m
Resources5m
Resources10m
Resources5m
Resources10m
5개 연습문제
Linear Search and Binary Search10m
Polynomial Multiplication15m
Master Theorem10m
Sorting15m
Quick Sort15m
4.7
1000개의 리뷰Chevron Right

36%

이 강좌를 수료한 후 새로운 경력 시작하기

36%

이 강좌를 통해 확실한 경력상 이점 얻기

13%

급여 인상 또는 승진하기

Algorithmic Toolbox의 최상위 리뷰

대학: SGJan 20th 2017

I liked the fact that the algorithms are not just the introductory searching and sorting algorithms. The assignments are fairly difficult (I have decent scripting experience), but not impossibly so.

대학: MMSep 29th 2017

good course, I like the fact you can use a lot of languages for you programming exercises, the content is really helpful, I would like to have more indications from the grading system to save time.

강사

Avatar

Alexander S. Kulikov

Visiting Professor
Department of Computer Science and Engineering
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Michael Levin

Lecturer
Computer Science
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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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Daniel M Kane

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

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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