Teaching

Introduction to programming for data analysis (with R)

Aix Marseille University · Master in Economics

Go to the course page

Applied Economics

Aix Marseille University · Master in economics, track “Data, Analysis, Decisions and Economic Evaluation”

Applied Economics Issues

Introduction Climate and the Economy: Introduction Climate and the Economy: IAMs Climate and the Economy: Assessing the Impacts Beliefs and Social Norms About Climate Change

Machine Learning

Aix Marseille University · Master in Economics, Econometrics / Big Data / Statistics Track

Machine Learning and Statistical Learning (AMU)

The 24 hours course alternates between lectures and practical sessions.

Week 1

• Introduction
  Slides
• Optimization problem: gradient descent
  Slides Code

Week 2

• Variants of the gradient descent algorithm
  Slides Code
• Hands-on session: preparing train and test datasets, overfitting
  Exercise
• Logistic regression
  Slides Exercise

Week 3

• K-nearest neighbors
  Slides Exercise
• Support Vector Machines
  Slides Exercise
• Hands-on: dealing with images
  Jupyter notebook to complete

Week 4

• Working with imbalanced datasets
  Notebook
• Explainability: Shap Values
  Slides Jupyter notebook
• Machine learning and ethics
  Slides

European Central Bank

Machine Learning Training (ECB)

Course by Emmanuel Flachaire, Professor of Economics at Aix-Marseille Université. Hands-on sessions by me.

Training organised by:

• Mario Porqueddu, Senior Economist, Prices and Costs Division, European Central Bank.
• Linda de Leeuw, Directorate General Economics, Prices & Costs Division, European Central Bank

Access the webpage of the course

R (old course)

Aix Marseille University · Undergraduate students in Economics

Here are some resources to learn how to use R (in French).

Course ebook

Course notes (HTML) PDF version

Hands-on sessions

Hands-on sessions

Old slides

• Introduction
  HTML Slides PDF Code
• Data
  HTML Slides PDF Code
• Tables
  HTML Slides PDF Code
• A few words on dates
  HTML Slides PDF
• Functions
  HTML Slides PDF Code
• Loops and apply functions
  HTML Slides PDF Code
• Graphs with ggplot2
  HTML Slides PDF Code
• Linear regression
  HTML Slides PDF Code

Python

Aix Marseille University · Magistère ingénieur économiste degree

Please find below an e-book for python beginners.

🇬🇧 English ebook 🇫🇷 French ebook

Templates for academic reports

I have prepared two templates for students’ academic reports: one using LaTeX only, and one using RMarkdown.

Using LaTeX

I assume that you are familiar with LaTeX.

Preview of the final output (PDF) Download the LaTeX template

Using RMarkdown

2.1 Resources

If you want to produce academic reports using RMarkdown, I have prepared a template which can generate either HTML or PDF reports.

🇬🇧 How to use RMarkdown 🇫🇷 Comment utiliser RMarkdown

2.2 Prior requirements

Some R packages are required: tidyverse, DT, kableExtra, knitr.

install.packages(c("tidyverse", "DT", "kableExtra", "knitr"))

In addition, to be able to compile the document to get the final output in a PDF format, a LaTeX engine is required:

tinytex::install_tinytex()

If you want to customize the theme, look in assets/style.css (HTML) or assets/style_rapport_amu.css (PDF).

2.3 Preview of the final output

HTML report PDF report

2.4 The template

Download the RMarkdown template