Course 6 : Introduction to causality
Lecture 6 : Lecture 6.pdf.
Notebook of Lecture 6 : Lecture6.ipynb. Data : hotel_bookings.csv
Lab 6 : Lab6pdf. Data : ihdp_npci.csv
Course 5: Interpretability
Lecture 5: Lecture 5.pdf.
Lab 5 : Lab5.pdf. Datasets : winequality.csv.
Notebook of Lab5 : Lab5.ipynb
Course 4: Introduction to neural networks
Lecture 4 : Lecture 4.pdf. Notebook : Lecture4.ipynb
Lab 4 : Lab4.pdf. Data : training_data.csv, test_data.csv.
Course 3: Decision Trees, Ensemble methods, Quantile regression
Lecture 3 Lecture 3.pdf.
Notebook of Lecture 3 : Lecture3.ipynb.
Lab 3 : Lab3.pdf. Datasets : FinancialDistress.csv
Course 2: Beyond OLS
Lecture 2: Lecture 2.pdf. Notebook : Lecture2.ipynb
Lab 2: Lab2.pdf. Dataset hitters.csv.
Course 1 : Basics on Random Variables with Python
First lectures on Random Variables : CM1a.pdf, CM1b.pdf. Notebook : Lecture1.ipynb
First lab : Lab1.pdf. Notebooks : Ex1.ipynb, Ex2_Ex3.ipynb
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
Complements to the Pandas library : ComplementsPandas.ipynb
Introduction to Python for data science : Tutorial or Other Tutorial
Install google colab : google colab
Use google colab : Tutorial
Import data on colab : Tutorial