linfo1121  2019-2020  Louvain-la-Neuve

Note from June 29, 2020
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
5 credits
30.0 h + 30.0 h
Q1

  This learning unit is not being organized during year 2019-2020.

Language
French
Prerequisites
This course assumes the mastery of programming and program design in an object-oriented language such as Java, knowledge of elementary data structures and notions of recursion and computational complexity as targeted by the course LEPL1402.

The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
Main themes
  • Complexity measures of an algorithm and complexity analysis methods.
  • Dichotomic sorting and search algorithms.
  • Basic data structures (lists, trees, binary search trees): study of their abstract properties, their concrete representations, their application and the main algorithms that manipulate them.
  • Advanced data structures (union-find, hash tables, heaps, balanced binary trees, graph representation and manipulation, textual data processing, dictionaries).
Aims

At the end of this learning unit, the student is able to :

1
Given the learning outcomes of the "Bachelor in Engineering" program, this course contributes to the development, acquisition and evaluation of the following learning outcomes:
  • AA1.1, AA1.2
  • AA2.4, AA2.5, AA2.7
  • AA3.2
  • AA4.3
Given the learning outcomes of the "Bachelor in Computer science" program, this course contributes to the development, acquisition and evaluation of the following learning outcomes:
  • S1.I1, S1.I3
  • S2.2, S2.3, S2.4
  • S4.3
  • S5.4
  • S6.1, S6.3
Students who have successfully completed this course will be able to :
  • make an informed choice on the use of the main data structures used to represent collections,
  • make good use of existing algorithms to manipulate these data structures and analyze their performance,
  • design and implement variants of the algorithms studied,
  • test algorithms and data structures,
  • make good use of algorithms and data structures documented in an API
  • abstract, model and implement effective solutions to algorithmic puzzle problems.
Students will have developed methodological and operational skills. In particular, they will have developed their ability to:
  • analyze critically a problem,
  • to test and debug algorithmic programs,
  • effectively implement short but non-trivial algorithms.learn for themselves in a reference book and in the complementary technical documentation
 

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Faculty or entity
INFO


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Specialization track in Computer Science

Bachelor in Computer Science