課程信息
265,001

第 1 門課程(共 6 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為34 小時

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

英語(English)

字幕:英語(English), 西班牙語(Spanish)

您將學到的內容有

  • Check

    Essential algorithmic techniques

  • Check

    Design efficient algorithms

  • Check

    Practice solving algorithmic interview problems

  • Check

    Implement efficient and reliable solutions

您將獲得的技能

Dynamic ProgrammingDebuggingSoftware TestingAlgorithmsComputer Programming

第 1 門課程(共 6 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為34 小時

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

英語(English)

字幕:英語(English), 西班牙語(Spanish)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 5 小時

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 個視頻 (總計 48 分鐘), 5 個閱讀材料, 3 個測驗
6 個視頻
Welcome!3分鐘
Solving the Sum of Two Digits Programming Challenge (screencast)6分鐘
Solving the Maximum Pairwise Product Programming Challenge: Improving the Naive Solution, Testing, Debugging13分鐘
Stress Test - Implementation8分鐘
Stress Test - Find the Test and Debug7分鐘
Stress Test - More Testing, Submit and Pass!8分鐘
5 個閱讀材料
Companion MOOCBook10分鐘
What background knowledge is necessary?10分鐘
Optional Videos and Screencasts10分鐘
Maximum Pairwise Product Programming Challenge10分鐘
Acknowledgements2分鐘
1 個練習
Solving Programming Challenges20分鐘
2
完成時間為 5 小時

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 個視頻 (總計 77 分鐘), 3 個閱讀材料, 4 個測驗
12 個視頻
Coming Up3分鐘
Problem Overview3分鐘
Naive Algorithm5分鐘
Efficient Algorithm3分鐘
Problem Overview and Naive Algorithm4分鐘
Efficient Algorithm5分鐘
Computing Runtimes10分鐘
Asymptotic Notation6分鐘
Big-O Notation6分鐘
Using Big-O10分鐘
Course Overview10分鐘
3 個閱讀材料
Resources2分鐘
Resources2分鐘
Resources2分鐘
3 個練習
Logarithms10分鐘
Big-O10分鐘
Growth rate10分鐘
3
完成時間為 4 小時

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 個視頻 (總計 56 分鐘), 1 個閱讀材料, 3 個測驗
10 個視頻
Car Fueling7分鐘
Car Fueling - Implementation and Analysis9分鐘
Main Ingredients of Greedy Algorithms2分鐘
Celebration Party Problem6分鐘
Efficient Algorithm for Grouping Children5分鐘
Analysis and Implementation of the Efficient Algorithm5分鐘
Long Hike6分鐘
Fractional Knapsack - Implementation, Analysis and Optimization6分鐘
Review of Greedy Algorithms2分鐘
1 個閱讀材料
Resources2分鐘
2 個練習
Greedy Algorithms10分鐘
Fractional Knapsack10分鐘
4
完成時間為 7 小時

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 個視頻 (總計 157 分鐘), 5 個閱讀材料, 6 個測驗
20 個視頻
Intro3分鐘
Linear Search7分鐘
Binary Search7分鐘
Binary Search Runtime8分鐘
Problem Overview and Naïve Solution6分鐘
Naïve Divide and Conquer Algorithm7分鐘
Faster Divide and Conquer Algorithm6分鐘
What is the Master Theorem?4分鐘
Proof of the Master Theorem9分鐘
Problem Overview2分鐘
Selection Sort8分鐘
Merge Sort10分鐘
Lower Bound for Comparison Based Sorting12分鐘
Non-Comparison Based Sorting Algorithms7分鐘
Overview2分鐘
Algorithm9分鐘
Random Pivot13分鐘
Running Time Analysis (optional)15分鐘
Equal Elements6分鐘
Final Remarks8分鐘
5 個閱讀材料
Resources10分鐘
Resources5分鐘
Resources10分鐘
Resources5分鐘
Resources10分鐘
5 個練習
Linear Search and Binary Search10分鐘
Polynomial Multiplication15分鐘
Master Theorem10分鐘
Sorting15分鐘
Quick Sort15分鐘
4.7
947 個審閱Chevron Right

35%

完成這些課程後已開始新的職業生涯

35%

通過此課程獲得實實在在的工作福利

13%

加薪或升職

熱門審閱

創建者 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.

創建者 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.

講師

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

關於 加州大学圣地亚哥分校

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....

關於 国立高等经济大学

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...

關於 数据结构与算法 專項課程

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....
数据结构与算法

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