2-Day Workshop - Introduction to Data Science in Python

Nov 28, 2019, 9:00 AM → Nov 29, 2019, 5:30 PM Europe/Paris

Room Grace Hoper (Inria Saclay Ile-de-France)

Guillaume Lemaitre (Inria), Jiaping Liu (Inria), Loic Esteve (Inria), Maria Telenczuk (Inria)

 

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 November 21.

Material and install

The material of the previous session 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. This material will be updated soon.

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, Jiaping Liu, Guillaume Lemaitre, Bartosz Telenczuk, Maria Telenczuk, Gaël Varoquaux.

Thu, November 28

9:00 AM → 9:30 AM General introduction: collect material and install

9:30 AM → 10:30 AM Introduction to NumPy

10:30 AM → 11:00 AM Coffee Break

11:00 AM → 12:30 PM Data wrangling using Pandas

12:30 PM → 2:00 PM Lunch Break

2:00 PM → 3:30 PM Data exploration using Pandas

3:30 PM → 4:00 PM Coffee Break

4:00 PM → 5:30 PM Data exploration using Pandas

Fri, November 29

9:00 AM → 10:30 AM Introduction to Machine Learning using scikit-learn

10:30 AM → 11:00 AM Coffee Break

11:00 AM → 12:30 PM Introduction to Machine Learning using scikit-learn

12:30 PM → 2:00 PM Lunch Break

2:00 PM → 3:30 PM Introduction to Machine Learning using scikit-learn

3:30 PM → 4:00 PM Coffee Break

4:00 PM → 5:30 PM Introduction to Machine Learning using scikit-learn