课程信息
4.7
3,784 个评分
836 个审阅
专项课程

第 1 门课程(共 6 门)

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

完成时间(小时)

完成时间大约为32 小时

建议:5 weeks of study, 4-8 hours/week...
可选语言

英语(English)

字幕:英语(English), 西班牙语(Spanish)

您将学到的内容有

  • Check

    Essential algorithmic techniques

  • Check

    Design efficient algorithms

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    Practice solving algorithmic interview problems

  • Check

    Implement efficient and reliable solutions

您将获得的技能

Dynamic ProgrammingDebuggingSoftware TestingAlgorithmsComputer Programming
专项课程

第 1 门课程(共 6 门)

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

完成时间(小时)

完成时间大约为32 小时

建议:5 weeks of study, 4-8 hours/week...
可选语言

英语(English)

字幕:英语(English), 西班牙语(Spanish)

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 5 小时

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....
Reading
6 个视频 (总计 48 分钟), 4 个阅读材料, 2 个测验
Video6 个视频
Welcome!3分钟
Solving the Sum of Two Digits Programming Challenges (screencast)6分钟
Solving the Maximum Pairwise Product Programming Challenge: Improving the Naive Solution, Testing, Debugging13分钟
Stress Test - Implementation8分钟
Stress Test - Find the Test and Debug7分钟
Stress Test - More Testing, Submit and Pass!8分钟
Reading4 个阅读材料
Companion MOOCBook10分钟
What background knowledge is necessary?10分钟
Optional Videos and Screencasts10分钟
Acknowledgements2分钟
Quiz1 个练习
Solving Programming Challenges20分钟
2
完成时间(小时)
完成时间为 6 小时

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!...
Reading
12 个视频 (总计 77 分钟), 3 个阅读材料, 4 个测验
Video12 个视频
Coming Up3分钟
Problem Overview3分钟
Naive Algorithm5分钟
Efficient Algorithm3分钟
Problem Overview and Naive Algorithm4分钟
Efficient Algorithm5分钟
Computing Runtimes10分钟
Asymptotic Notation6分钟
Big-O Notation6分钟
Using Big-O10分钟
Course Overview10分钟
Reading3 个阅读材料
Resources2分钟
Resources2分钟
Resources2分钟
Quiz3 个练习
Logarithms10分钟
Big-O10分钟
Growth rate10分钟
3
完成时间(小时)
完成时间为 4 小时

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....
Reading
10 个视频 (总计 56 分钟), 1 个阅读材料, 3 个测验
Video10 个视频
Car Fueling7分钟
Car Fueling - Implementation and Analysis9分钟
Main Ingredients of Greedy Algorithms2分钟
Celebration Party Problem6分钟
Efficient Algorithm for Grouping Children5分钟
Analysis and Implementation of the Efficient Algorithm5分钟
Long Hike6分钟
Fractional Knapsack - Implementation, Analysis and Optimization6分钟
Review of Greedy Algorithms2分钟
Reading1 个阅读材料
Resources2分钟
Quiz2 个练习
Greedy Algorithms10分钟
Fractional Knapsack10分钟
4
完成时间(小时)
完成时间为 7 小时

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!...
Reading
20 个视频 (总计 157 分钟), 5 个阅读材料, 6 个测验
Video20 个视频
Intro3分钟
Linear Search7分钟
Binary Search7分钟
Binary Search Runtime8分钟
Problem Overview and Naïve Solution6分钟
Naïve Divide and Conquer Algorithm7分钟
Faster Divide and Conquer Algorithm6分钟
What is the Master Theorem?4分钟
Proof of the Master Theorem9分钟
Problem Overview2分钟
Selection Sort8分钟
Merge Sort10分钟
Lower Bound for Comparison Based Sorting12分钟
Non-Comparison Based Sorting Algorithms7分钟
Overview2分钟
Algorithm9分钟
Random Pivot13分钟
Running Time Analysis (optional)15分钟
Equal Elements6分钟
Final Remarks8分钟
Reading5 个阅读材料
Resources10分钟
Resources5分钟
Resources10分钟
Resources5分钟
Resources10分钟
Quiz5 个练习
Linear Search and Binary Search10分钟
Polynomial Multiplication15分钟
Master Theorem10分钟
Sorting15分钟
Quick Sort15分钟
4.7
836 个审阅Chevron Right
职业方向

29%

完成这些课程后已开始新的职业生涯
工作福利

83%

通过此课程获得实实在在的工作福利
职业晋升

11%

加薪或升职

热门审阅

创建者 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.

创建者 AGFeb 19th 2018

best course for clearing basics of algorithms as well as learning by doing and blow your mind by thinking hard from different prospectives to get desired solutions of programming assignments ...

讲师

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

关于 University of California San Diego

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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...

关于 Data Structures and Algorithms 专项课程

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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