Context
Data from Rouen University services. Those data is about campus france application at Rouen for 2019. But identifications features are all anonymize (please check original version to see it)
This dataset (v1.capuse_france_rouen_dataset) base on the original dataset(which is also upload here) collect informations about international students that have applied for campus france admission in 2019. Those data is only about 2019 and the aim is to collect the maximum informations about candidate learning levels and the university commission decision about their application.
Content
What's inside is more than just rows and columns. I've remove ID row because it doesn't have any specific informations.
- Libellé formation de la candidature : the field where the candidate apply
- Année d'entrée de la candidature : the degree candidate have applied for. 1 for master 1, 2 for Licence 2 and 3 for Licence 3
- Avis SCAC: favorable or not
- Niveau du dernier diplôme obtenu : last graduate level
- Moyenne du dernier diplôme obtenu : note of last graduate
- Appréciation SCAC sur cursus : SCAS appreciation about candidate school curriculum
- Capacité à se faire comprendre : capacity of candidate to make himself understand
- Capacité à comprendre : capacity of candidate to understand
- Etat de la candidature : application result
Check this link to better understand SCAS : http://etudier-en-france.fr/avis-scac/
Acknowledgements
Self learning data science i do believe that "the best way to learn is to give".
Inspiration
How far can we how what make Rouen University commision to select or not a future lectures? What are the similarity and the dissimilarity between those selected and those rejected? How well can we predict the future candidate result base on theirs informations?
Feel free to contact me if you have any questions.
my linkedIn : williams AVOCE
mail : canisius.avoce@outlook.com
Or kindly ask Rouen university services
Thanks and good job all.