DebuggingSoftware TestingAlgorithmsData StructureComputer ProgrammingDynamic ProgrammingBinary Search TreePriority QueueHash TableStack (Abstract Data Type)ListGraph Theory
Spécialisation Structures de données et algorithmes
Master Algorithmic Programming Techniques. Learn algorithms through programming and advance your software engineering or data science career
Offert par
Université de Californie à San Diego
Université nationale de recherche, École des hautes études en sciences économiques
Spécialisation Structures de données et algorithmesUniversité de Californie à San DiegoCe que vous allez apprendre
Apply basic algorithmic techniques such as greedy algorithms, binary search, sorting and dynamic programming to solve programming challenges.
Apply various data structures such as stack, queue, hash table, priority queue, binary search tree, graph and string to solve programming challenges.
Apply graph and string algorithms to solve real-world challenges: finding shortest paths on huge maps and assembling genomes from millions of pieces.
Solve complex programming challenges using advanced techniques: maximum flow, linear programming, approximate algorithms, SAT-solvers, streaming.
Compétences que vous acquerrez
À propos de ce Spécialisation
170,568 consultations récentes
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.
Projet d'apprentissage appliqué
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.
Résultats de carrière des étudiants
37 %
ont commencé une nouvelle carrière après avoir terminé ce spécialisation.
25 %
ont obtenu une augmentation de salaire ou une promotion.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
Cours en ligne à 100 %
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Planning flexible
Définissez et respectez des dates limites flexibles.
Niveau intermédiaire
Basic knowledge of at least one programming language: C++, Java, Python, C, C#, Javascript, Haskell, Kotlin, Ruby, Rust, Scala. Basic knowledge of discrete mathematics: proof by induction, proof by contradiction.
Approx. 8 mois pour terminer
6 heures/semaine recommandées
Anglais
Sous-titres : Anglais, Espagnol, Français, Portugais (brésilien), Russe
Résultats de carrière des étudiants
37 %
ont commencé une nouvelle carrière après avoir terminé ce spécialisation.
25 %
ont obtenu une augmentation de salaire ou une promotion.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
Cours en ligne à 100 %
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Planning flexible
Définissez et respectez des dates limites flexibles.
Niveau intermédiaire
Basic knowledge of at least one programming language: C++, Java, Python, C, C#, Javascript, Haskell, Kotlin, Ruby, Rust, Scala. Basic knowledge of discrete mathematics: proof by induction, proof by contradiction.
Approx. 8 mois pour terminer
6 heures/semaine recommandées
Anglais
Sous-titres : Anglais, Espagnol, Français, Portugais (brésilien), Russe
Cette Spécialisation compte 6 cours
Algorithmic Toolbox
9,275 évaluations
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).
structures de données
3,532 évaluations
A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures.
Algorithms on Graphs
1,783 évaluations
If you have ever used a navigation service to find optimal route and estimate time to destination, you've used algorithms on graphs. Graphs arise in various real-world situations as there are road networks, computer networks and, most recently, social networks! If you're looking for the fastest time to get to work, cheapest way to connect set of computers into a network or efficient algorithm to automatically find communities and opinion leaders in Facebook, you're going to work with graphs and algorithms on graphs.
Algorithmes sur les chaînes
886 évaluations
World and internet is full of textual information. We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. To make sense of all that information and make search efficient, search engines use many string algorithms. Moreover, the emerging field of personalized medicine uses many search algorithms to find disease-causing mutations in the human genome.
Offert par
Université de Californie à 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.
Université nationale de recherche, École des hautes études en sciences économiques
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.
Foire Aux Questions
Puis-je obtenir des crédits universitaires si je réussis la Spécialisation ?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Can I just enroll in a single course?
Si vous vous abonnez, vous bénéficiez d'une période d'essai gratuite de 7 jours, durant laquelle vous pouvez annuler votre abonnement sans pénalité. Ensuite, nous n'accordons plus de remboursements, mais vous pouvez annuler votre abonnement à tout instant. Consultez notre politique de remboursement complète.
Puis-je m'inscrire à un seul cours ?
Oui ! Pour commencer, cliquez sur la carte du cours qui vous intéresse et inscrivez-vous. Vous pouvez vous inscrire et terminer le cours pour obtenir un Certificat partageable, ou vous pouvez accéder au cours en auditeur libre afin d'en visualiser gratuitement le contenu. Si vous vous abonnez à un cours faisant partie d'une Spécialisation, vous êtes automatiquement abonné(e) à la Spécialisation complète. Visitez votre tableau de bord d'étudiant(e) pour suivre vos progrès.
Can I take the course for free?
Oui, Coursera offre une Aide Financière aux étudiants qui n'ont pas les moyens d'acquitter les frais. Demandez-la en cliquant sur le lien Aide Financière sous le bouton S'inscrire situé à gauche. Vous devrez remplir un formulaire de demande et vous serez averti(e) si elle est acceptée. Vous devrez répéter cette procédure pour chaque cours de la Spécialisation, y compris pour le Projet Final. En savoir plus.
Puis-je suivre le cours gratuitement ?
Si vous vous inscrivez au cours, vous pouvez accéder à tous les cours de la Spécialisation et obtenir un Certificat lorsque vous terminez le travail. Si vous souhaitez seulement lire et examiner le contenu du cours, vous pouvez accéder gratuitement au cours en auditeur libre. Si vous n'avez pas les moyens d'acquitter les frais, vous pouvez faire une demande d'Aide Financière.
Ce cours est-il vraiment accessible en ligne à 100 % ? Dois-je assister à certaines activités en personne ?
Ce cours est entièrement en ligne : vous n'avez donc pas besoin de vous présenter physiquement dans une salle de classe. Vous pouvez accéder à vos vidéos de cours, lectures et devoirs en tout temps et en tout lieu, par l'intermédiaire du Web ou de votre appareil mobile.
What background knowledge is necessary?
1. Basic knowledge of at least one programming language: C++, Java, Python, C, C#, Javascript, Haskell, Kotlin, Ruby, Rust, Scala.
We expect you to be able to implement programs that: 1) read data from the standard input (in most cases, the input is a sequence of integers); 2) compute the result (in most cases, a few loops are enough for this); 3) print the result to the standard output. For each programming challenge in this course, we provide starter solutions in C++, Java, and Python. The best way to check whether your programming skills are enough to go through problems in this specialization is to solve two problems from the first week. If you are able to pass them (after reading our tutorials), then you will definitely be able to pass the course.
2. Basic knowledge of discrete mathematics: proof by induction, proof by contradiction.
Knowledge of discrete mathematics is necessary for analyzing algorithms (proving correctness, estimating running time) and for algorithmic thinking in general. If you want to refresh your discrete mathematics skills, we encourage you to go through our partner specialization — Introduction to Discrete Mathematics for Computer Science (https://www.coursera.org/specializations/discrete-mathematics). It teaches the basics of discrete mathematics in try-this-before-we-explain-everything approach: you will be solving many interactive puzzles that were carefully designed to allow you to invent many of the important ideas and concepts yoursel
What is the difference between this course and other courses covering algorithms?
We believe that learning the theory behind algorithms (like in most Algorithms 101 courses taught at 1000s universities) is important but not sufficient for a professional computer scientist today. This specialization combines the theory of algorithms with many programming challenges. In contrast with many Algorithms 101 courses, you will implement over 100 algorithmic problems in the programming language of your choice. And you will see yourself that the best way to understand an algorithm is to implement it!
How long does it take to complete the Specialization?
Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 6-8 months.
Quelle est la durée nécessaire pour terminer la Spécialisation ?
Each course in the Specialization is offered on a regular schedule, with sessions starting about once per month. If you don't complete a course on the first try, you can easily transfer to the next session, and your completed work and grades will carry over.
À quelle fréquence chaque cours de cette Spécialisation est-il proposé ?
Basic knowledge of at least one programming language (C/C++, Java, Python): loops, arrays, stacks, recursion. Basic knowledge of mathematics: proof by induction, proof by contradiction.
Do I need to take the courses in a specific order?
We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.
Will I earn university credit for completing the Specialization?
Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
Puis-je obtenir des crédits universitaires si je réussis la Spécialisation ?
The lectures in this specialization will be self-contained. Most lectures will be based on the bestselling textbook "Algorithms" co-authored by Sanjoy Dasgupta from University of California at San Diego as well as Christos Papadimitriou and Umesh Vazirani from University of California at Berkeley. In addition to UCSD and Berkeley, the textbook has been adopted in over 100 top universities and is available on Internet.
D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.
