Since 2021 I am teaching two fall courses of the second year of the Master in Collective Intelligence at UM6P.
Programming, Data Science and Statistics 3 (PDSS 3)
This module covers various scientific computing techniques and is designed to equip the students of the MSc programme in Collective Intelligence with different methods useful in computation, modelling and analysis of complex systems. PDSS3 Syllabus
Decision making & Leadership Lab
In this course students learn multiple theories of organizational behavior and everyday leadership and apply them to actual cases of organizational change. We also explore dynamics of individual and group decision making and the challenges of managing motivation, competing interests and emerging ethical issues an increasingly complex and changing world. LL Syllabus
Here I make public a teaching portfolio that summarises a coherent set of materials representing my view of teaching as a scholarly activity, my professional experience and pedagogical training as well as some examples of course design.
This section contains a variety of materials that I have developed and adapted for my seminars on research methods, agent based models and data collection and processing.
Research methods: Linear models and mixed effects models in R
Research methods using R
Twitter data collection and analysis using R
Agent based models
Lab 5: Building a simple agent based model
Lab 6: Generating data using a cultral evolutionary model. In this lab we will use a version of the model published in Cognitive Science: