Course 2 : Basics on visualization and linear algebra with Python
Introduction to data visualization with the Seaborn library : IntroductionSeaborn.ipynb
A website on Exploratory Data Analysis with seaborn : https://www.geeksforgeeks.org/box-plot-visualization-with-pandas-and-seaborn/
Linear algebra refresher : LinearAlgebraRefresher.ipynb
A website : https://towardsdatascience.com/basics-of-linear-algebra-for-data-science-9e93ada24e5c
Second lecture on Random Variables : CM_RandomVariables3.pdf. Notebook of the Lecture : Lecture3.ipynb. Dataset : iris.csv
Exploratory Data Analysis : EDA1.pdf. The dataset Ames House : AmesHouseDataset.csv
Exploratory Data Analysis 2: EDA2.pdf. Dataset : titanic.csv
Course 1 : Basics on Random Variables with Python
First lecture on Random Variables : Lecture1.pdf. Notebook of Lecture 1 : Lecture1.ipynb
Practical Session 1 : PracticalSession1.pdf.
Data : DataAirLiquide.csv
Basics on Python
Introduction to Python : IntroductionPython.ipynb
Introduction to the Numpy library: IntroductionNumpy.ipynb
Introduction to the Pandas library : IntroductionPandas.ipynb. The dataset president_heights.csv
Introduction to Python for data science : Tutorial or Other Tutorial
Additional material