Python for Data Science
Teacher
ECTS:
2
Course Hours:
0
Tutorials Hours:
21
Language:
French
Examination Modality:
mém+sout.
Objective
Python has recently become a more than convincing alternative for scientists and as it is a generic language, it is possible to manage all the processing applied to data, from data source processing to data visualization without changing the language. This course introduces different tools that allow you to make the data "speak" in order to quickly obtain results.
Planning
Part 1: Handling Data
* Introduction:
Back to the basics of Python,
Presentation of the Python Ecosystem for Data Science
Introduction to good practices
Presentation of the principles of data-science
* Handling structured data :
Basic principles with numpy
Manipulate databases with pandas and SQL
Introduction to spatial data (geopandas)
* Handle less traditional data:
Retrieve data by webscraping and APIs
Manipulate text data
Part 2: View
* Presentation of the basic packages for graphics:
matplotlib, seaborn
* Cartography:
still maps
dynamic maps (HTML)
Part 3: Modeling
* General models:
Regression
CPA
Machine Learning with sklearn
* Natural Language Processing
* Deepening of Machine Learning models
References
Site web du cours: https://pythonds.linogaliana.fr/
Tous les codes sources sont disponibles sur Github: https://github.com/linogaliana/python-datascientist
Tous les chapitres du cours sont disponibles sur le site web et disponibles sous format notebook dans divers environnement (SSP Cloud, Google Colab, Binder, Visual studio dev...).
Les éléments relatifs à l'évaluation sont dans la section dédiée
Un ensemble de référence est disponible dans la section dédiée
La présentation faite en amphithéâtre est disponible ici