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)