Informações sobre o curso
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Nível intermediário


Legendas: Inglês, Espanhol

O que você vai aprender

  • Check

    Essential algorithmic techniques

  • Check

    Design efficient algorithms

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    Practice solving algorithmic interview problems

  • Check

    Implement efficient and reliable solutions

Habilidades que você terá

Dynamic ProgrammingDebuggingSoftware TestingAlgorithmsComputer Programming

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário


Legendas: Inglês, Espanhol

Programa - O que você aprenderá com este curso

5 horas para concluir

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 vídeos ((Total 48 mín.)), 5 leituras, 3 testes
6 videos
Solving the Sum of Two Digits Programming Challenge (screencast)6min
Solving the Maximum Pairwise Product Programming Challenge: Improving the Naive Solution, Testing, Debugging13min
Stress Test - Implementation8min
Stress Test - Find the Test and Debug7min
Stress Test - More Testing, Submit and Pass!8min
5 leituras
Companion MOOCBook10min
What background knowledge is necessary?10min
Optional Videos and Screencasts10min
Maximum Pairwise Product Programming Challenge10min
1 exercício prático
Solving Programming Challenges20min
5 horas para concluir

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 vídeos ((Total 77 mín.)), 3 leituras, 4 testes
12 videos
Coming Up3min
Problem Overview3min
Naive Algorithm5min
Efficient Algorithm3min
Problem Overview and Naive Algorithm4min
Efficient Algorithm5min
Computing Runtimes10min
Asymptotic Notation6min
Big-O Notation6min
Using Big-O10min
Course Overview10min
3 leituras
3 exercícios práticos
Growth rate10min
4 horas para concluir

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 vídeos ((Total 56 mín.)), 1 leitura, 3 testes
10 videos
Car Fueling7min
Car Fueling - Implementation and Analysis9min
Main Ingredients of Greedy Algorithms2min
Celebration Party Problem6min
Efficient Algorithm for Grouping Children5min
Analysis and Implementation of the Efficient Algorithm5min
Long Hike6min
Fractional Knapsack - Implementation, Analysis and Optimization6min
Review of Greedy Algorithms2min
1 leituras
2 exercícios práticos
Greedy Algorithms10min
Fractional Knapsack10min
7 horas para concluir


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 vídeos ((Total 157 mín.)), 5 leituras, 6 testes
20 videos
Linear Search7min
Binary Search7min
Binary Search Runtime8min
Problem Overview and Naïve Solution6min
Naïve Divide and Conquer Algorithm7min
Faster Divide and Conquer Algorithm6min
What is the Master Theorem?4min
Proof of the Master Theorem9min
Problem Overview2min
Selection Sort8min
Merge Sort10min
Lower Bound for Comparison Based Sorting12min
Non-Comparison Based Sorting Algorithms7min
Random Pivot13min
Running Time Analysis (optional)15min
Equal Elements6min
Final Remarks8min
5 leituras
5 exercícios práticos
Linear Search and Binary Search10min
Polynomial Multiplication15min
Master Theorem10min
Quick Sort15min
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Principais avaliações do Algorithmic Toolbox

por 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.

por 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.



Alexander S. Kulikov

Visiting Professor
Department of Computer Science and Engineering

Michael Levin

Computer Science

Neil Rhodes

Adjunct Faculty
Computer Science and Engineering

Pavel Pevzner

Department of Computer Science and Engineering

Daniel M Kane

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

Sobre Universidade da Califórnia, 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....

Sobre 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 communicamathematics, engineering, and more. Learn more on

Sobre o Programa de cursos integrados Estruturas de dados e algoritmos

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....
Estruturas de dados e algoritmos

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

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