Teacher(s)
Bogaert Patrick (coordinator); Hanert Emmanuel;
Language
English
> French-friendly
> French-friendly
Prerequisites
This project is open to any bioengineer master student (A, C, E or F) upon prior completion of the bachelor cycle.
Main themes
The integrated project in Data Science requires the students from option 10 - Data Science - to mobilize their knowledge and skills in an integrated and transverse way whatever their specific master. The goal is to understand and analyze a problem which is relevant to the field of bioengineering and that involves data of various nature and sources.
The project will cover topics that address the whole information processing chain, including data acquisition, data processing and communication issues directed towards various public or private stakeholders.
The complexity and deadlines of the project correspond to situations that are expected to arise in a real professional context. The project will involve both written and oral communication of the results that can be understood and use by non-specialists.
The project will cover topics that address the whole information processing chain, including data acquisition, data processing and communication issues directed towards various public or private stakeholders.
The complexity and deadlines of the project correspond to situations that are expected to arise in a real professional context. The project will involve both written and oral communication of the results that can be understood and use by non-specialists.
Learning outcomes
At the end of this learning unit, the student is able to : | |
1 |
|
Content
Each year, a different real-world and topical problem will be presented to the students. This presentation may involve various stakeholders. In order to mimic a real engineering office, the students will organize themselves into groups that are composed of 2 to 4 students. They will summarize the problem and plan the work to be done (steps and milestones, external resources to be used, deadlines to honor) in order to achieve a scientifically sound and realistic solution.
Depending on the problem at hand, the work will include at least two priority tasks among the following list (other tasks are thus considered as subordinated) : data collection, data validation & correction, management of the corresponding databases, statistical analyses and modeling, risk analysis about the project outcomes and proposed solution, written and oral communication towards stakeholders and scientists that are non-specialists, assistance for a proper diffusion of the results (indicators, computer interfaces, etc.).
The students will have to report the intermediate outcomes of the project at key steps. A joint written report must be delivered by the end of the semester. This report will be orally presented during the examination session.
Depending on the problem at hand, the work will include at least two priority tasks among the following list (other tasks are thus considered as subordinated) : data collection, data validation & correction, management of the corresponding databases, statistical analyses and modeling, risk analysis about the project outcomes and proposed solution, written and oral communication towards stakeholders and scientists that are non-specialists, assistance for a proper diffusion of the results (indicators, computer interfaces, etc.).
The students will have to report the intermediate outcomes of the project at key steps. A joint written report must be delivered by the end of the semester. This report will be orally presented during the examination session.
Teaching methods
Students will work jointly within in a group and will be supervised on a weekly basis by the teaching team.
Evaluation methods
Written report and oral presentation of the results at the end of the project. As the project is a group activity and is evaluated as is, it can only be presented during the first examination session.
Other information
This course can be given in English and French.
Faculty or entity
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Environmental Bioengineering