Course Overview

The generalized use of data and smart digital systems heralds a new
digital age: from digital nomadism and intelligent cities to a better
understanding of human needs and uses. These future systems, dedicated
to the analysis, recognition and optimization of resources, pave the
way to life-changing applications, but require a broad scientific
knowledge and skills in digital sciences. The NUMERICS course proposes
training in mathematics, computer science and science for engineers,
combinedwith human and social sciences to prepare the experts of the
future in these domain. 

Learning Achievement

Competence

Course prerequisites

Any student with excellent scores in any numerical science
(mathematics, computer science, engineering) can apply to this
interdisciplinary module. 
Students should be able to read documents written in English and
follow courses and scientific talks in English. 

Grading Philosophy

Assessment will be based on the oral presentation of results obtained
by the small group of students during the thematic week (50%) and the
individual scientific report written by each student on a topic to be
chosen among the methods and scientific challenges studied during the
course (50%). 

- The presentation will take place in January.  - The report is
due in April. - There will be no repeat session. 

Course schedule

The two proposed thematic weeks for 2021-2021 address: 

- The Internet of Things : conception and realization of an embedded
system, management of this system through some network, treatment of
collected data, interpretation of the results, social and ethic
aspects. - Optimization and decision : combining methods from
combinatorial optimization, modelling, mathematical programming, deep
learning to tackle problems arising in industry  - The scientific
seminars will address all scientific, ethical, human and social
aspects of numerical sciences. 

Course type

Lectures, keynotes, lab work, group project, seminars, personal research and redaction under the supervision of a mentor. - In-class : courses, keynotes, seminars, workshops.  - Face-to-face :  work in small groups mentored by experts during the thematic week and along the year with the mentor.  - Distance-based : discovery of the labs, redaction of a scientific report with support and advice from a tutor, personal work during the weeks, preparation of the presentation

Online Course Requirement

Instructor

Other information

The maximum number of students is 80.Applicants will be selected
according to demonstrated skills, academic excellence, professonal and
scientific project.Evaluation will be based on the presentation of
achievements met during the thematic week and the scientific report.Duration: One thematic week to be chosen
Study level: Multi-level
Language of instruction: English and French
Mode of delivery: Blended learning

Site for Inquiry