The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second).
Ce cours fait partie de la Spécialisation Data Structures and Algorithms
Algorithmic Toolbox
proposé par
University of California San Diego
National Research University Higher School of Economics
À propos de ce cours
4.7
3,700 notes
Compétences que vous acquerrez
AlgorithmsDynamic ProgrammingGreedy AlgorithmDivide And Conquer Algorithms
Programme du cours : ce que vous apprendrez dans ce cours
Semaine
1Programming 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 vidéos (Total 48 min), 4 lectures, 2 quiz
6 vidéos
Welcome!3 min
Solving the Sum of Two Digits Programming Challenges (screencast)6 min
Solving the Maximum Pairwise Product Programming Challenge: Improving the Naive Solution, Testing, Debugging13 min
Stress Test - Implementation8 min
Stress Test - Find the Test and Debug7 min
Stress Test - More Testing, Submit and Pass!8 min
4 lectures
Companion MOOCBook10 min
What background knowledge is necessary?10 min
Optional Videos and Screencasts10 min
Acknowledgements2 min
1 exercice pour s'entraîner
Solving Programming Challenges20 min
Semaine
2Algorithmic 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 vidéos (Total 77 min), 3 lectures, 4 quiz
12 vidéos
Coming Up3 min
Problem Overview3 min
Naive Algorithm5 min
Efficient Algorithm3 min
Problem Overview and Naive Algorithm4 min
Efficient Algorithm5 min
Computing Runtimes10 min
Asymptotic Notation6 min
Big-O Notation6 min
Using Big-O10 min
Course Overview10 min
3 lectures
Resources2 min
Resources2 min
Resources2 min
3 exercices pour s'entraîner
Logarithms10 min
Big-O10 min
Growth rate10 min
Semaine
3Greedy 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 vidéos (Total 56 min), 1 lecture, 3 quiz
10 vidéos
Largest Number2 min
Car Fueling7 min
Car Fueling - Implementation and Analysis9 min
Main Ingredients of Greedy Algorithms2 min
Celebration Party Problem6 min
Efficient Algorithm for Grouping Children5 min
Analysis and Implementation of the Efficient Algorithm5 min
Long Hike6 min
Fractional Knapsack - Implementation, Analysis and Optimization6 min
Review of Greedy Algorithms2 min
1 lecture
Resources2 min
2 exercices pour s'entraîner
Greedy Algorithms10 min
Fractional Knapsack10 min
Semaine
4Divide-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 vidéos (Total 157 min), 5 lectures, 6 quiz
20 vidéos
Intro3 min
Linear Search7 min
Binary Search7 min
Binary Search Runtime8 min
Problem Overview and Naïve Solution6 min
Naïve Divide and Conquer Algorithm7 min
Faster Divide and Conquer Algorithm6 min
What is the Master Theorem?4 min
Proof of the Master Theorem9 min
Problem Overview2 min
Selection Sort8 min
Merge Sort10 min
Lower Bound for Comparison Based Sorting12 min
Non-Comparison Based Sorting Algorithms7 min
Overview2 min
Algorithm9 min
Random Pivot13 min
Running Time Analysis (optional)15 min
Equal Elements6 min
Final Remarks8 min
5 lectures
Resources10 min
Resources5 min
Resources10 min
Resources5 min
Resources10 min
5 exercices pour s'entraîner
Linear Search and Binary Search10 min
Polynomial Multiplication15 min
Master Theorem10 min
Sorting15 min
Quick Sort15 min
4.7
817 avis29%
83%
11%
Meilleurs avis
par SG•Jan 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.
par AG•Feb 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 ...
Enseignants
Alexander S. Kulikov
Visiting ProfessorDepartment of Computer Science and Engineering
Michael Levin
LecturerComputer Science
Neil Rhodes
Adjunct FacultyComputer Science and Engineering
Pavel Pevzner
ProfessorDepartment of Computer Science and Engineering
Daniel M Kane
Assistant ProfessorDepartment of Computer Science and Engineering / Department of Mathematics
À propos de University of California 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.
À propos de 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
À propos de la Spécialisation Data Structures and Algorithms
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.
Foire Aux Questions
Quand aurai-je accès aux vidéos de cours et aux devoirs ?
Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.
À quoi ai-je droit si je m'abonne à cette Spécialisation ?
Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.
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