CS-250 / 6 crédits

Enseignant: Svensson Ola Nils Anders

Langue: Anglais


Summary

The students learn the theory and practice of basic concepts and techniques in algorithms. The course covers mathematical induction, techniques for analyzing algorithms, elementary data structures, major algorithmic paradigms such as dynamic programming, sorting and searching, and graph algorithms.

Content

Keywords

algorithms, data structures, efficiency, problem solving

Learning Prerequisites

Recommended courses

Advanced ICC I

Learning Outcomes

By the end of the course, the student must be able to:

  • Illustrate the execution of algorithms on example inputs
  • Describe basic data structures such as arrays, lists, stacks, queues, binary search trees, heaps, and hash tables
  • Analyze algorithm efficiency
  • Compare alternative algorithms and data structures with respect to efficiency
  • Choose which algorithm or data structure to use in different scenarios
  • Use algorithms and data structures taught in the course on concrete problem instances
  • Design new algorithms and data structures based on known methods
  • Prove the correctness of an algorithm

Teaching methods

Ex cathedra lecture, exercises in classroom

Assessment methods

Continuous assessment with final exam.

Resources

Bibliography

Thomas Cormen, Charles Leiserson, Ronald Rivest, Clifford Stein: Introduction to algorithms, Third Edition, MIT Press, 2009.

 

Ressources en bibliothèque

Dans les plans d'études

  • Semestre: Automne
  • Forme de l'examen: Ecrit (session d'hiver)
  • Matière examinée: Algorithms
  • Cours: 4 Heure(s) hebdo x 14 semaines
  • Exercices: 2 Heure(s) hebdo x 14 semaines
  • Semestre: Automne
  • Forme de l'examen: Ecrit (session d'hiver)
  • Matière examinée: Algorithms
  • Cours: 4 Heure(s) hebdo x 14 semaines
  • Exercices: 2 Heure(s) hebdo x 14 semaines
  • Semestre: Automne
  • Forme de l'examen: Ecrit (session d'hiver)
  • Matière examinée: Algorithms
  • Cours: 4 Heure(s) hebdo x 14 semaines
  • Exercices: 2 Heure(s) hebdo x 14 semaines
  • Semestre: Automne
  • Forme de l'examen: Ecrit (session d'hiver)
  • Matière examinée: Algorithms
  • Cours: 4 Heure(s) hebdo x 14 semaines
  • Exercices: 2 Heure(s) hebdo x 14 semaines
  • Semestre: Automne
  • Forme de l'examen: Ecrit (session d'hiver)
  • Matière examinée: Algorithms
  • Cours: 4 Heure(s) hebdo x 14 semaines
  • Exercices: 2 Heure(s) hebdo x 14 semaines
  • Semestre: Automne
  • Forme de l'examen: Ecrit (session d'hiver)
  • Matière examinée: Algorithms
  • Cours: 4 Heure(s) hebdo x 14 semaines
  • Exercices: 2 Heure(s) hebdo x 14 semaines
  • Semestre: Automne
  • Forme de l'examen: Ecrit (session d'hiver)
  • Matière examinée: Algorithms
  • Cours: 4 Heure(s) hebdo x 14 semaines
  • Exercices: 2 Heure(s) hebdo x 14 semaines
  • Semestre: Automne
  • Forme de l'examen: Ecrit (session d'hiver)
  • Matière examinée: Algorithms
  • Cours: 4 Heure(s) hebdo x 14 semaines
  • Exercices: 2 Heure(s) hebdo x 14 semaines
  • Semestre: Automne
  • Forme de l'examen: Ecrit (session d'hiver)
  • Matière examinée: Algorithms
  • Cours: 4 Heure(s) hebdo x 14 semaines
  • Exercices: 2 Heure(s) hebdo x 14 semaines
  • Semestre: Automne
  • Forme de l'examen: Ecrit (session d'hiver)
  • Matière examinée: Algorithms
  • Cours: 4 Heure(s) hebdo x 14 semaines
  • Exercices: 2 Heure(s) hebdo x 14 semaines

Semaine de référence

 LuMaMeJeVe
8-9     
9-10     
10-11     
11-12     
12-13     
13-14    CO1
14-15SG1   
15-16    
16-17GCA331
GCB330
GCB331
GRA330
GRB330
    
17-18    
18-19     
19-20     
20-21     
21-22     

Vendredi, 13h - 15h: Cours CO1

Lundi, 14h - 16h: Cours SG1

Lundi, 16h - 18h: Exercice, TP GCA331
GCB330
GCB331
GRA330
GRB330