Coursebooks 2017-2018

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Caution, these contents corresponds to the coursebooks of last year


Algorithms

CS-250

Lecturer(s) :

Kapralov Mikhail

Language:

English

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

Mathematical Induction

Analysis of Algorithms

Data structures

Design of algorithms by induction

Greedy Algorithms

Sorting and searching

Graphs algorithms and data structures

Complexity

Keywords

algorithms, data structures, efficiency, problem solving

Learning Prerequisites

Recommended courses

Discrete Structures

Learning Outcomes

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

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
Websites

In the programs

  • Computer Science, 2017-2018, Bachelor semester 3
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      6
    • Subject examined
      Algorithms
    • Lecture
      4 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
  • Mathematics, 2017-2018, Bachelor semester 5
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      6
    • Subject examined
      Algorithms
    • Lecture
      4 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
  • Passerelle HES - IN, 2017-2018, Autumn semester
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      6
    • Subject examined
      Algorithms
    • Lecture
      4 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
  • Passerelle HES - SC, 2017-2018, Autumn semester
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      6
    • Subject examined
      Algorithms
    • Lecture
      4 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
  • Computational science and Engineering, 2017-2018, Master semester 1
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      6
    • Subject examined
      Algorithms
    • Lecture
      4 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
  • Computational science and Engineering, 2017-2018, Master semester 3
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      6
    • Subject examined
      Algorithms
    • Lecture
      4 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
  • Communication Systems, 2017-2018, Bachelor semester 3
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      6
    • Subject examined
      Algorithms
    • Lecture
      4 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
  • Information security minor, 2017-2018, Autumn semester
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      6
    • Subject examined
      Algorithms
    • Lecture
      4 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks
  • Computer science minor, 2017-2018, Autumn semester
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      6
    • Subject examined
      Algorithms
    • Lecture
      4 Hour(s) per week x 14 weeks
    • Exercises
      2 Hour(s) per week x 14 weeks

Reference week

MoTuWeThFr
8-9
9-10
10-11
11-12
12-13
13-14 CO1
14-15CE6
15-16
16-17GCA331
GCB330
GCB331
GCD0386
GRA330
17-18
18-19
19-20
20-21
21-22
Lecture
Exercise, TP
Project, other

legend

  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German