Over the past six months, ICES training courses have been put on hold as traditionally, our courses have taken place in physical settings – whether that is in ICES Headquarters in Copenhagen or onboard a research vessel.
If our course participants cannot come to us, then we will come to them - and our training courses are making the move online, with two courses already on offer for 2020.
The first course, fish stock assessment models with focus on State-space Assessment Model (SAM) and Template Model Building (TMB), will take place 12–16 October.
Anders Nielsen, DTU-Aqua, and
Olav Nikolai Breivik, Norwegian Computing Centre, will
train scientists in setting up assessment models, and then correctly interpret the results. "During the course we will elaborate on how SAM is implemented in TMB, states Breivik, "This will allow us to demonstrate how to modify configurations in SAM which should provide an intuitive understanding of state space assessment models".
TMB is a tool that efficiently setting up highly parameterized models possibly including random effects. Breivik continues, "By elaborating the mathematics and statistics behind SAM, and how to implement models in TMB, participants will strengthen their skills in both developing/expanding state space models and applying SAM".
Bayesian Network analysis and the social-cultural dimension will take place 7–11 December, run by
Laura
Uusitalo, Finnish Environment Institute, and Päivi
Haapasaari, University of Helsinki.
Having applied Bayesian networks in both inter- and transdisciplinary studies, the trainers found that the method works well in integrated analyses. “The ecosystem approach to fisheries management requires recognizing and analyzing coupled social-ecological systems and involving stakeholders in management processes", notes Haapasaari, "We also think that the method provides possibilities for further developing different types of holistic analyses”. And this course is aimed at researchers who want to deal with holistic analyses involving social aspects.
"Both natural scientists and social scientists are very welcome, says Haapasaari, "We have found that Bayesian networks can facilitate understanding complex problems from different viewpoints, and that they also facilitate learning across disciplinary boundaries”.
Uusitalo states that participants will learn how to formulate their research problem as a Bayesian network, and how to quantify and analyze the model. "They’ll learn the basics of Bayesian inference, and how to build models that are theoretically sound as well as practically solvable.”
The online training consists of online meetings, video lectures, own reading and hands-on work on your own Bayesian model. The course requires that the participants can dedicate the whole week for it.
Uusitalo explains that some of the time is used for online group meetings, but there will be also a lot of reading materials, exercises, and working on your own model.
Register for both courses now.