2-Day Workshop - Introduction to Data Science in Python

Europe/Paris
Room Grace Hoper (Inria Saclay Ile-de-France)

Room Grace Hoper

Inria Saclay Ile-de-France

1 Rue Honoré d'Estienne d'Orves 91120 Palaiseau
Balázs Kégl (LAL), Guillaume Lemaitre (Inria), Joris Van den Bossche (Inria), Maria Telenczuk (Inria)
Description

 

Data science is gaining attention impacting many scientific fields and applications. Data science encompasses a large number of topics such as data mining, data wrangling, data visualisation, pattern recognition, or machine learning.

This workshop intends to give an introduction to some of these topics using Python and the PyData ecosystem. It is not a course on deep learning.

Program

Day 1 - Data wrangling, exploration, and visualisation

Goal: introduce the PyData ecosystem to manipulate, explore, and visualize data.

  • Introduction to the basics of numpy, pandas, and matplotlib.

Day 2 - Machine learning

Goal: introduce the basics of machine learning using the  scikit-learn library.

  • Get familiar with general principles of machine learning;

  • Use these principles by using the scikit-learn library on some toy and real-world data examples.

Registration

The 2-day workshop is aimed at graduate students and researchers, who have a basic knowledge of Python or have experience in another scientific programming language such as R or Matlab.

Registration is free but mandatory due to limited space (see the link below to register). Registration will close on March 4.

Material and install

The material can be found on the GitHub page of the Paris-Saclay Center for Data Science. Refer to the README file regarding the information to install the required packages which will be used during the workshop.

Location

This workshop will take place in Inria Saclay Ile-de-France (1 Rue Honoré d'Estienne d'Orves, 91120 Palaiseau, room Grace Hoper.

Instructors

Loïc Esteve, Alexandre Gramfort, Balazs Kegl, Guillaume Lemaitre, Bartosz Telenczuk, Maria Telenczuk, Joris Van den Bossche, Gaël Varoquaux.

  • Wednesday, 13 March
    • 09:00 09:30
      General introduction: collect material and install
    • 09:30 10:30
      Introduction to NumPy
    • 10:30 11:00
      Coffee Break 30m
    • 11:00 12:30
      Data wrangling using Pandas
    • 12:30 14:00
      Lunch Break 1h 30m
    • 14:00 15:30
      Data exploration using Pandas
    • 15:30 16:00
      Coffee Break 30m
    • 16:00 17:30
      Data exploration using Pandas
  • Thursday, 14 March
    • 09:00 10:30
      Introduction to Machine Learning using scikit-learn
    • 10:30 11:00
      Coffee Break 30m
    • 11:00 12:30
      Introduction to Machine Learning using scikit-learn
    • 12:30 14:00
      Lunch Break 1h 30m
    • 14:00 15:30
      Introduction to Machine Learning using scikit-learn
    • 15:30 16:00
      Coffee Break 30m
    • 16:00 17:30
      Introduction to Machine Learning using scikit-learn
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