We teach courses for the Master's in Data Science at the University of Helsinki, organize workshops and tutorials in statistical model fitting, and provide other teaching material such as a guide to writing Master's theses.

Taught Courses at the University of Helsinki

Ongoing courses (academic year 2023/24)

  • Computational Statistics (MAST32001). Period I, Autumn term. Taught yearly from Autumn 2021. Course description.
  • Computational Statistics, self-study version (MAST32001). Period III-IV, Spring term, online teaching. Taught yearly from Spring 2022. Course description.
  • Probabilistic Cognitive Modelling (DATA20047). Period III, Spring term. Taught yearly from Spring 2023. Course description.

Past courses

Guide to Writing Master's Theses

I wrote a guide to writing Master's theses, mostly targeted at (my) students of the Master's programme in Data Science of the University of Helsinki—but possibly of broader interest.

International Tutorials and Workshops

We have been regularly giving classes, tutorials, and workshops at summer schools and for research groups at various institutions worldwide, for a duration that ranges from 20 minutes to 4+ hours. Typical topics include optimization (and our BADS toolbox), Bayesian model fitting (and our VBMC toolbox), and model comparison.

As representative examples:

  • The module on computational modeling and statistical model fitting taught at the University of Geneva in Spring 2020, as part of the graduate course Trends in Computational Neuroscience. Slides and Python notebook (link).
  • Lectures on optimization and Bayesian inference for statistical model fitting given in 2022 at the Barcelona summer school for Advanced Modeling of Behavior (BAMB! 2022). Slides and MATLAB code (link).

We also like to play around with visualizations for demonstration purposes. This is a demo we built of several optimizers at work (link).


    List of past workshops:

    1. Joint Ma-Niv-Pillow lab meeting, Princeton University (Princeton, NJ, Sep 2015).
    2. IISDM decision making joint lab meeting, New York University (New York, NY, May 2016).
    3. Alex Pouget’s lab, University of Geneva (Geneva, Switzerland, Sep 2016).
    4. Konrad Kording’s lab, Northwestern University (Chicago, IL, Jun 2017).
    5. Andreas Tolias’s lab, Baylor’s College of Medicine (Houston, TX – in telepresence, Jul 2017).
    6. CoSMo summer school 2017, University of Minnesota (Minneapolis, MN, Aug 2017). Code: https://github.com/lacerbi/cosmo-2017-tutorial
    7. NYU Training Program in Computational Neuroscience, New York University (New York, NY, Sep 2017).
    8. CoSMo summer school 2018, University of Minnesota (Minneapolis, MN, Aug 2018). Code: https://github.com/lacerbi/cosmo-2018-tutorial
    9. Bristol Neuroscience Group, University of Bristol (Bristol, UK, May 2019). Code: https://github.com/lacerbi/workshop-bristol-2019
    10. International Brain Laboratory code camp, Columbia University (New York, NY, Sep 2019).
    11. Center for Neural Science, New York University (New York, NY, Sep 2019). Code: https://github.com/lacerbi/workshop-nyu-2019
    12. Psychology department, Stockholm University (Stockholm, Sweden, Nov 2019).
    13. Trends in Computational Neuroscience graduate course; Department of Neuroscience, University of Geneva (Geneva, Apr 2020). Website: https://github.com/lacerbi/tics-2020-tutorial
    14. IBL Computational Neuroscience course, International Brain Laboratory (Apr 2020).
    15. BAMB! 2022 - Barcelona summer school for Advanced Modeling of Behavior, Barcelona Biomedical Research Park (Barcelona, Spain, Sep 2022). Code: https://github.com/lacerbi/bamb2022-model-fitting