Deadline approaching: Data Wrangling with Tidyverse for Ecologists in flexible online format at SMSC

[NZCBI-SCBI Training]

The application deadline (Feb 12) is fast approaching for our online professional training course: Managing Ecological Data in R: Introduction to Data Science and the Art of Wrangling for Ecologists. We do expect this course to fill to capacity before the application deadline, so we encourage anyone interested to apply and register as soon as possible to secure your seat. Remember that only registration (not course acceptance) guarantees your place in the course. Scholarships are available for applicants outside of Europe and North America. Just tick the relevant box in your application and if you are eligible you will be considered. You statement of interest will be considered a major factor in your scholarship application review. You must apply by February 12 to be considered for a scholarship to this program. Numerous scholarships are available so we encourage you to apply even if you do not have funding available.

 

Managing Ecological Data in R: Introduction to Data Science and the Art of Wrangling for Ecologists

• Dates: March 11 – May 5, 2024

• Cost: 500.00 USD
• Deadline: February 12, 2024

 

Description: Wrangling and manipulating datasets can be one of the biggest hurdles to overcome in analyzing and publishing your research. In many cases, researchers and students spend more time organizing, formatting and cleaning data then they do actually using it to answer their research questions. Yet there are many tools available, particularly in the R environment, to make this stage of your research efficient, and error-free. In addition, R provides numerous tools to streamline and professionalize communication of your results. As big data increasingly becomes a component of ecological study, there is a developing need for understanding how to maintain large and complex datasets, prepare data for analysis, and develop a reproducible workflow.

 

Dr. Brian Evans has designed this course to create a flexible toolbox for ecologists and environmental scientists who seek to better manage and use data. Over 8 weeks participants will explore the management of ecological data using Program R. They will focus on the structure and linguistics of data in R, how to integrate R into a modern data science workflow, and explore how to think about ecological data in new ways. Participants will gain an in-depth understanding of the tidyverse package. Through this process, participants will develop a flexible skillset for managing and exploring data. Each weekly module will consist of recorded lectures and guided lab activities using real world ecological applications. R packages used in the course will include tidyr, dplyr, lubridate, stringr, and purr among others. See our course page for a complete list of course topics. Note that this course is not recommended for those not familiar with working in the R environment.