Teaching Resources
Below is a selection of courses for which I have developed open-access materials. For a complete list of my teaching experience, please refer to my CV.
- Machine Learning for Molecular Design (2023)
- Repsol Technology Lab
- An almost self-contained crash course on applying Machine Learning to molecular discovery.
- Course Website
- Data Analysis (2022–2023)
- CUNEF University
- Undergraduate course for Economics and Computer Science students.
- Course Website (Spanish)
- Bayesian Methods in Artificial Intelligence (2021)
- Institute of Mathematical Sciences (ICMAT-CSIC)
- Taught at the JAE Intro School. Covers Bayesian inference fundamentals and applications in AI.
Slides and Labs Video Recordings
- Machine Learning: Foundations and Applications (2021)
- Institute of Mathematical Sciences (ICMAT-CSIC)
- Taught at the JAE Intro School.
Slides and Labs Video Recordings
- Practical Machine Learning with R (2019)
- National Statistics Institute (INE)
- Training course for statistical staff.
- Slides and Exercises (Spanish)
- Applications of Stochastic Processes (2019–2020)
- Complutense University of Madrid
- Undergraduate course for Mathematics and Economics students.
- Course Notes (Spanish)
