April 2020
ONLINE COURSE – Introduction to Bayesian hierarchical modelling using R (IBHM04) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential. Course Overview: This course will cover introductory hierarchical modelling for real-world data sets from a Bayesian perspective. These methods lie at the forefront of statistics research and are a vital…
Find out more »ONLINE COURSE – Generalised Linear (MIXED) (GLMM), Nonlinear (NLGLM) And General Additive Models (MIXED) (GAMM) (GNAM01) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential. Course Overview: Course Overview: This course provides a general introduction to nonlinear regression analysis, covering major topics including, but not limited to, general and generalized linear models, generalized additive models,…
Find out more »May 2020
ONLINE COURSE – Python for data science, machine learning, and scientific computing (PDMS02) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential. Course Overview: Python is one of the most widely used and highly valued programming languages in the world, and is especially widely used in data science, machine learning, and in…
Find out more »ONLINE COURSE – Reproducible Data Science using RMarkdown, Git, R packages, Docker, Make & Drake, and other tools (RDRP01) This course will be delivered live
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak. This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential. Course Overview: This course provides a comprehensive introduction to doing reproducible data analysis, which we define as analysis where the entire workflow or pipeline is as open and transparent as…
Find out more »Fuzzy logic to address gradual patterns in species distribution and diversity (FLDD01)
Course Overview: Live beings are constantly in motion and occur with varying frequency across space. Hence, categorical occurrence maps are always incomplete and oversimplified representations of species’ actual distributions. Analyses that build on such categorical data, such as most diversity, overlap and (dis)similarity indices, overlook important gradations in species occurrence. Fuzzy logic is a valuable tool to formally address the locational uncertainty and gradual variations that characterize biodiversity patterns. This course will show how fuzzy logic can be incorporated in…
Find out more »Structural Equation Modelling for Ecologists and Evolutionary Biologists (SEMR03) FREE ACCOMMODATION AVAILABLE
Course Overview: The course is a primer on structural equation modelling (SEM) and confirmatory path analysis, with an emphasis on practical skills and applications to real-world data. Structural equation modelling is a rapidly growing technique in ecology and evolution that unites multiple hypotheses in a single causal network. It provides an intuitive graphical representation of relationships among variables, underpinned by well-described mathematical estimation procedures. Several advances in SEM over the past few years have expanded its utility for typical ecological…
Find out more »June 2020
Landscape genetic data analysis using R (LNDG04)
Course Overview: The term ‘landscape genetics’ has been applied studies that integrate ecological context and intervening landscape into population genetic analyses of contemporary processes such as gene flow and migration. This course will cover the basics of both quantitative landscape ecology and population genetics, focusing on how we develop and evaluate spatial/genetic analyses using the R platform. Intended Audience This course is suitable for graduate students, postdoctoral researchers, and primary investigators interested in learning how to integrate landscape ecological and…
Find out more »Stable Isotope Mixing Models using SIBER, SIAR, MixSIAR (SIMM06)
Course overview: This course will cover the concepts, technical background and use of stable isotope mixing models (SIMMs) with a particular focus on running them in R. This course will cover the concepts, technical background and use of stable isotope mixing models (SIMMs) with a particular focus on running them in R. Recently SIMMs have become a very popular tool for quantifying food webs and thus the diet of predators and prey in an ecosystem. Starting with only basic understanding…
Find out more »July 2020
Applied Bayesian modelling for ecologists and epidemiologists (ABME06)
Course Overview: This application-driven course will provide a founding in the basic theory & practice of Bayesian statistics, with a focus on MCMC modeling for ecological & epidemiological problems. Starting from a refresher on probability & likelihood, the course will take students all the way to cutting-edge applications such as state-space population modelling & spatial point-process modelling. By the end of the week, you should have a basic understanding of how common MCMC samplers work and how to program them,…
Find out more »Species Distribution Modeling using R (SDMR02)
Course Overview: If you are interested in gaining the introductory knowledge required to work with SDMs, whether you be a student, postdoc, or practicing scientist, this course is for you.This four-day course will provide participants with the background knowledge and skills needed to get started in the use of species distribution models (SDMs) for applied and basic research. The course will focus on (1) the preparation of required spatial datasets (biological observations and environmental predictors); (2) practical considerations in the…
Find out more »October 2020
Ecological niche modelling using R (ENMR04)
Course Overview: The course will cover the base theory of ecological niche modelling and its main methodologies. By the end of this 5-day practical course, attendees will have the capacity to perform ecological niche models and understand their results, as well as to choose and apply the correct methodology depending on the aim of their type of study and data. Ecological niche, species distribution, habitat distribution, or climatic envelope models are different names for similar mechanistic or correlative models, empirical…
Find out more »Advanced Ecological Niche Modelling Using R (ANMR01)
Course Overview: Ecological niche, species distribution, habitat distribution, or climatic envelope models are different names for mechanistic and correlative models, which are empirical or mathematical approaches to the ecological niche of a species. These methods relate different types of ecogeographical variables (environmental, topographical, human) to species physiological data or geographical locations, in order to identify the factors limiting and defining the species' niche. ENMs have become popular because of their efficiency in the design and implementation of conservation management. Have…
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