Objectives of Programme's Learning Outcomes

• Understand the fundamentals of computer science
• Show an understanding and deep knowledge of the concepts of computer science and mathematical formalisms used in the field of computer science
• Use the vocabulary and the correct mathematical reasoning to formulate and solve problems in the field of computer science
• Understand computer technologies
• Understand the IT involved in the different stages of the life of a computer application
• Self-train in ICT
• Demonstrate basic knowledge and know-how in related fields
• Demonstrate knowledge and basic skills in science and technology.
• Understand the fundamentals related to scientific methods
• Develop skills of abstraction and modelling through a conceptual and scientific approach
• Conduct rigorous reasoning based on scientific arguments
• Understand the fundamentals of communication
• Communicate information (both orally and in writing) relating to the field of computer science in an intelligible, clear and structured way
• Communicate a consistent and rigorous scientific argument, either orally or in writing

Learning Outcomes of UE

Understand the fundamental notions and problems appearing in graph theory;study the corresponding algorithms;go deeply into algorithmic notions from the algorithm efficiency point of view;understand the fundamental problems and techniques of combinatorial optimization;illustrate some methods on some particular problems;show the utility of algorithms for solving practical problems in scheduling management, logistics,...

Content of UE

Basic notions of graph theory and data structure; study of classical graph theory problems : trees, shortest paths, connexity, flows;introduction to complexity theory : P and NP classes; study of classical combinatorial optimization problems : knapsack, set covering, travelling salesman; introduction to metaheuristics.

The teaching methods are likely to be adjusted according to the educational context
imposed by the health measures.
 

Prior Experience

Linear programming; duality; notion of algorithm.

Type of Assessment for UE in Q1

• Presentation and/or works
• Written examination

Q1 UE Assessment Comments

The report and the presentation of the projet/challenge (part of the AA) accounting for  20% of the evaluation.
The absence at the presentation of the project/challenge (and/or not submitting the report) implies an absence on the whole of the UE.
Written examination in person covering both parts of the course: Graph theory  : (theory and exercises)  40% Combinatorial optimization : (theory and exercises)  40%.

The evaluation procedures are likely to be adjusted according to
the educational/assessment context imposed by health measures.

Type of Assessment for UE in Q3

• Presentation and/or works
• Written examination

Q3 UE Assessment Comments

The report and the presentation of the projet/challenge (part of the AA) accounting for  20% of the evaluation.
The absence at the presentation of the project/challenge (and/or not submitting the report) implies an absence on the whole of the UE.
Written examination in person covering both parts of the course: Graph theory  : (theory and exercises)  40% Combinatorial optimization : (theory and exercises)  40%.

The evaluation procedures are likely to be adjusted according to
the educational/assessment context imposed by health measures.

Type of Resit Assessment for UE in Q1 (BAB1)

• N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable