À propos de ce cours
21,281 consultations récentes

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.

Niveau avancé

Approx. 23 heures pour terminer

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


Sous-titres : Anglais

Compétences que vous acquerrez

Python ProgrammingLinear Programming (LP)Np-CompletenessDynamic Programming

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.

Niveau avancé

Approx. 23 heures pour terminer

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


Sous-titres : Anglais

Programme du cours : ce que vous apprendrez dans ce cours

5 heures pour terminer

Flows in Networks

Network flows show up in many real world situations in which a good needs to be transported across a network with limited capacity. You can see it when shipping goods across highways and routing packets across the internet. In this unit, we will discuss the mathematical underpinnings of network flows and some important flow algorithms. We will also give some surprising examples on seemingly unrelated problems that can be solved with our knowledge of network flows.

9 vidéos (Total 72 min), 3 lectures, 2 quiz
9 vidéos
Network Flows9 min
Residual Networks10 min
Maxflow-Mincut7 min
The Ford–Fulkerson Algorithm7 min
Slow Example3 min
The Edmonds–Karp Algorithm11 min
Bipartite Matching11 min
Image Segmentation7 min
3 lectures
Slides and Resources on Flows in Networks10 min
Available Programming Languages10 min
FAQ on Programming Assignments10 min
1 exercice pour s'entraîner
Flow Algorithms10 min
5 heures pour terminer

Linear Programming

Linear programming is a very powerful algorithmic tool. Essentially, a linear programming problem asks you to optimize a linear function of real variables constrained by some system of linear inequalities. This is an extremely versatile framework that immediately generalizes flow problems, but can also be used to discuss a wide variety of other problems from optimizing production procedures to finding the cheapest way to attain a healthy diet. Surprisingly, this very general framework admits efficient algorithms. In this unit, we will discuss some of the importance of linear programming problems along with some of the tools used to solve them.

10 vidéos (Total 84 min), 1 lecture, 2 quiz
10 vidéos
Linear Programming8 min
Linear Algebra: Method of Substitution5 min
Linear Algebra: Gaussian Elimination10 min
Convexity9 min
Duality12 min
(Optional) Duality Proofs7 min
Linear Programming Formulations8 min
The Simplex Algorithm10 min
(Optional) The Ellipsoid Algorithm6 min
1 lecture
Slides and Resources on Linear Programming10 min
1 exercice pour s'entraîner
Linear Programming Quiz10 min
5 heures pour terminer

NP-complete Problems

Although many of the algorithms you've learned so far are applied in practice a lot, it turns out that the world is dominated by real-world problems without a known provably efficient algorithm. Many of these problems can be reduced to one of the classical problems called NP-complete problems which either cannot be solved by a polynomial algorithm or solving any one of them would win you a million dollars (see Millenium Prize Problems) and eternal worldwide fame for solving the main problem of computer science called P vs NP. It's good to know this before trying to solve a problem before the tomorrow's deadline :) Although these problems are very unlikely to be solvable efficiently in the nearest future, people always come up with various workarounds. In this module you will study the classical NP-complete problems and the reductions between them. You will also practice solving large instances of some of these problems despite their hardness using very efficient specialized software based on tons of research in the area of NP-complete problems.

16 vidéos (Total 115 min), 2 lectures, 2 quiz
16 vidéos
Search Problems9 min
Traveling Salesman Problem7 min
Hamiltonian Cycle Problem8 min
Longest Path Problem1 min
Integer Linear Programming Problem3 min
Independent Set Problem3 min
P and NP4 min
Reductions5 min
Showing NP-completeness6 min
Independent Set to Vertex Cover5 min
3-SAT to Independent Set14 min
SAT to 3-SAT7 min
Circuit SAT to SAT12 min
All of NP to Circuit SAT5 min
Using SAT-solvers14 min
2 lectures
Slides and Resources on NP-complete Problems10 min
Minisat Installation Guide10 min
1 exercice pour s'entraîner
NP-complete Problems12 min
5 heures pour terminer

Coping with NP-completeness

After the previous module you might be sad: you've just went through 5 courses in Algorithms only to learn that they are not suitable for most real-world problems. However, don't give up yet! People are creative, and they need to solve these problems anyway, so in practice there are often ways to cope with an NP-complete problem at hand. We first show that some special cases on NP-complete problems can, in fact, be solved in polynomial time. We then consider exact algorithms that find a solution much faster than the brute force algorithm. We conclude with approximation algorithms that work in polynomial time and find a solution that is close to being optimal.

11 vidéos (Total 119 min), 1 lecture, 2 quiz
11 vidéos
2-SAT10 min
2-SAT: Algorithm12 min
Independent Sets in Trees14 min
3-SAT: Backtracking11 min
3-SAT: Local Search12 min
TSP: Dynamic Programming15 min
TSP: Branch and Bound9 min
Vertex Cover9 min
Metric TSP12 min
TSP: Local Search6 min
1 lecture
Slides and Resources on Coping with NP-completeness10 min
1 exercice pour s'entraîner
Coping with NP-completeness6 min
69 avisChevron Right


a commencé une nouvelle carrière après avoir terminé ces cours


a bénéficié d'un avantage concret dans sa carrière grâce à ce cours


a obtenu une augmentation de salaire ou une promotion

Principaux examens pour Advanced Algorithms and Complexity

par EMJan 4th 2018

As usual, complex arguments explained in simple terms!\n\nSome problems are really tough! (e.g. there's a problem from Google Code Jam).\n\nThank you for this course!

par ASJun 15th 2018

Another great course in this specialization with challenging and interesting assignments. However, this one is somewhat harder but rewarding.



Alexander S. Kulikov

Visiting Professor
Department of Computer Science and Engineering

Michael Levin

Computer Science

Daniel M Kane

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

Neil Rhodes

Adjunct Faculty
Computer Science and Engineering

À propos de 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....

À propos de 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. Learn more on www.hse.ru...

À propos de la Spécialisation Structures de données et algorithmes

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....
Structures de données et algorithmes

Foire Aux Questions

  • 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.

  • 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.

D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.