このコースについて
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自分のスケジュールですぐに学習を始めてください。

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中級レベル

約34時間で修了

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

英語

字幕:英語, スペイン語

学習内容

  • Check

    Essential algorithmic techniques

  • Check

    Design efficient algorithms

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    Practice solving algorithmic interview problems

  • Check

    Implement efficient and reliable solutions

習得するスキル

Dynamic ProgrammingDebuggingSoftware TestingAlgorithmsComputer Programming

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

約34時間で修了

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

英語

字幕:英語, スペイン語

シラバス - 本コースの学習内容

1
5時間で修了

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件のビデオ (合計48分), 5 readings, 3 quizzes
6件のビデオ
Solving the Sum of Two Digits Programming Challenge (screencast)6 分
Solving the Maximum Pairwise Product Programming Challenge: Improving the Naive Solution, Testing, Debugging13 分
Stress Test - Implementation8 分
Stress Test - Find the Test and Debug7 分
Stress Test - More Testing, Submit and Pass!8 分
5件の学習用教材
Companion MOOCBook10 分
What background knowledge is necessary?10 分
Optional Videos and Screencasts10 分
Maximum Pairwise Product Programming Challenge10 分
Acknowledgements2 分
1の練習問題
Solving Programming Challenges20 分
2
5時間で修了

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件のビデオ (合計77分), 3 readings, 4 quizzes
12件のビデオ
Coming Up3 分
Problem Overview3 分
Naive Algorithm5 分
Efficient Algorithm3 分
Problem Overview and Naive Algorithm4 分
Efficient Algorithm5 分
Computing Runtimes10 分
Asymptotic Notation6 分
Big-O Notation6 分
Using Big-O10 分
Course Overview10 分
3件の学習用教材
Resources2 分
Resources2 分
Resources2 分
3の練習問題
Logarithms10 分
Big-O10 分
Growth rate10 分
3
4時間で修了

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件のビデオ (合計56分), 1 reading, 3 quizzes
10件のビデオ
Car Fueling7 分
Car Fueling - Implementation and Analysis9 分
Main Ingredients of Greedy Algorithms2 分
Celebration Party Problem6 分
Efficient Algorithm for Grouping Children5 分
Analysis and Implementation of the Efficient Algorithm5 分
Long Hike6 分
Fractional Knapsack - Implementation, Analysis and Optimization6 分
Review of Greedy Algorithms2 分
1件の学習用教材
Resources2 分
2の練習問題
Greedy Algorithms10 分
Fractional Knapsack10 分
4
7時間で修了

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件のビデオ (合計157分), 5 readings, 6 quizzes
20件のビデオ
Intro3 分
Linear Search7 分
Binary Search7 分
Binary Search Runtime8 分
Problem Overview and Naïve Solution6 分
Naïve Divide and Conquer Algorithm7 分
Faster Divide and Conquer Algorithm6 分
What is the Master Theorem?4 分
Proof of the Master Theorem9 分
Problem Overview2 分
Selection Sort8 分
Merge Sort10 分
Lower Bound for Comparison Based Sorting12 分
Non-Comparison Based Sorting Algorithms7 分
Overview2 分
Algorithm9 分
Random Pivot13 分
Running Time Analysis (optional)15 分
Equal Elements6 分
Final Remarks8 分
5件の学習用教材
Resources10 分
Resources5 分
Resources10 分
Resources5 分
Resources10 分
5の練習問題
Linear Search and Binary Search10 分
Polynomial Multiplication15 分
Master Theorem10 分
Sorting15 分
Quick Sort15 分
4.7
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Algorithmic Toolbox からの人気レビュー

by 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.

by 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

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データ構造とアルゴリズムの専門講座について

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....
データ構造とアルゴリズム

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