linfo1101  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
Language
French
Main themes
  • Introduction to programming;
  • The Python programming language;
  • Analysis of a computer science problem, design, specification and implementation of a solution;
  • Linear data structures;
  • Fundamental concepts of object-oriented programming.
Aims

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

1
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.I2
  • S2.2, S2.4

Students who have successfully completed this course will be able to :

  • Apply the concepts and reasoning in the discipline of computer science to a problem of delimited complexity.
  • Describe the tools, techniques and computations needed to solve this disciplinary problem.
  • Model a problem and design one or more technical solutions that respect the specifications.
  • Implement and test a solution in the form of a prototype.
  • Work in pairs or in group and commit collectively to a work plan, a timetable (and roles to play).
  • Communicate in graphical and schematic form, be able to interpret diagrams, present the results of a work, structure information.
  • Read, analyse and exploit technical documents (standards, plans, specifications, specifications, ...).
  • Write written summary documents taking into account the requirements of the missions (projects and problems).
  • Demonstrate a good understanding of the concepts and methodology of programming, including object-oriented programming.
  • Make good use of the elements of an programming language like Python, including its object-oriented concepts.
 

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”.
Content
  • Programs, source code and program execution
  • Identifiers, variables, values, types, assignment
  • Expressions, instructions
  • Conditional structures and loops
  • Functions, parameters, calls, results, execution, variable scoping
  • Specifications and tests
  • Modules
  • Data structures, lists, strings and their operations
  • References and nested data structures
  • Nestsed lists, tuples, matrices, dictionnaries
  • Dichotomic search algorithms
  • File handling, input/output
  • Exception handling
  • Object-oriented programming and garbage collection
  • Classes, objects, constructors, methods
  • References to an object, self-references and self-calls
  • Class, instance and local variables, scope, visibility
  • Class composition, inheritance and encapsulation
  • Polymorphism, super calls and dynamic binding
  • Object equality
  • Linked data structures
Teaching methods
The teaching methods used will encourage active student learning, through a mixture of :
  • lectures,
  • partical exercice sessions with tutors,
  • programming exercices on the INGInious platform.
Evaluation methods
A mid-term evaluation will take place in the middle of the first semester. The score obtained for this exam will count for 1/3 of the final grade, but only if it is greater than the examination mark.
The end-term exam aims to assess both the understanding of the course material and the capacity to apply it to correctly write simple Python programs.
Online resources
All course material: slides, syllabus and exercices will be made available online.
Faculty or entity


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

Title of the programme
Sigle
Credits
Prerequisites
Aims
Certificat d'université : Statistique et sciences des données (15/30 crédits)

Bachelor in Mathematics

Master [120] in Linguistics

Bachelor in Computer Science

Master [120] in Data Science : Statistic

Approfondissement en statistique et sciences des données

Approfondissement en sciences et technologies de l'information et de la communication (pour seule réinscription)

Additionnal module in Geography

Minor in Computer Sciences

Minor in Statistics, Actuarial Sciences and Data Sciences

Minor in Information and Communication Studies and Technologies