Lecturer

Intro to Data Science I (Autumn 2025): I taught this course for master’s students in Actuarial Sciences at the University of Lausanne, introducing data science in Python and best practices for reproducible workflows. Lectures combined interactive slides, live coding, and practical introductions to tools such as Quarto and GitHub. The course materials are available as the open-source book DSAS: Data Science for Actuarial Sciences in Python.

• 📖 Course Book (DSAS)
• 📑 Sample Slide (Numpy)
• ⭐ Teaching Evaluations

Graduate Assistant

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Additionally, I serve as a graduate assistant for several courses at UNIL. The focus usually is on using R and Python as programming languages to train data scientists who can share reproducible workflows. Aside from these two languages, students learn about tools such as Quarto, Git, and, occasionally, shell scripting.

• Machine Learning in Business Analytics (MLBA) - Spring 2022, 2023, 2024, 2025: I created & maintained the completely open-source course website do-unil.github.io/mlba. My duties include leading lab sessions in R & Python, as well as teaching polyglot programming. Although I teach technical tools, the emphasis is on the right approach to applied/research projects, regardless of the specific tools the students choose.

• Data Science in Business Analytics - Autumn 2024 and 2025: This course focuses on data analysis, wrangling, and visualization. I lead the exercises in Python (pre-2025, in R) and teach students about reporting, dashboarding, and using Quarto. I also mentor and coach students on their projects.

• Text Mining - Autumn 2022, 2023: I developed and delivered lab sessions and lectures covering encoding and web scraping. The course mixed theory with practical demos of neural language processing. Below is a sample of my web scraping session (Nov 2022):