Generative AI is rapidly transforming how we work, communicate, and conduct research. For researchers, support staff, and professionals across disciplines, understanding how to strategically use tools like ChatGPT and other large language models (LLMs) is becoming essential.
This introductory training is designed to equip participants with a foundational understanding of generative AI, its practical applications, and its limitations.
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Effective research data management (RDM) is more than just a compliance requirement - it's a practical tool that simplifies your workflow, strengthens your research, and enhances the impact of your publications. This training is designed to help researchers integrate RDM practices into their projects from the outset, always keeping the publication process in mind.
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With the advances in technology, understanding the volume of information and giving it meaning is becoming increasingly challenging. We will utilize Gene Ontology and Gene enrichment, as well as Pathways, to interpret our data and unravel the meaning of our gene set. This introductory course will elucidate the biology behind the gene and clarify what your data means.
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The container workshop will provide an introduction to Docker and Apptainer, which are great components for achieving the portability and reproducibility of your analysis.
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In this half-day introduction, you will have the opportunity to know a bit more about the structure of the HPC (tiers), what resources you have available, and most importantly, how to use and navigate the HPC.
In this course, you will learn the differences and similarities between
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In this course, you will learn from A to Z about how to design a FAIR training material. You will be challenged to work in a group to build a FAIR lesson on a topic to be presented at the end of the course. Come inspired!
It is based on the FAIR training handbook from ELIXIR and 10 simple rules to make material FAIR publication. All sessions are structured to complement each other, aiming to introduce participants to a theoretical & hands-on approach to designing FAIR training material.
Effective research data management (RDM) is more than just a compliance requirement - it's a practical tool that simplifies your workflow, strengthens your research, and enhances the impact of your publications. This training is designed to help researchers integrate RDM practices into their projects from the outset, always keeping the publication process in mind.
Objectives
This course is designed for researchers and support staff who are new to version control and want to adopt best practices for managing code and collaborating on scientific projects. As research becomes increasingly computational, using free tools like Git and GitHub is essential for tracking changes, ensuring reproducibility, and working efficiently in teams. In this hands-on session, you will learn how to set up Git, manage your project history, and collaborate using GitHub.
Join us to brainstorm the challenges and solutions of data analysis reproducibility. No matter your background or level of expertise, this is a great opportunity for exchange, improving critical thinking, problem-solving, and interaction with experts.
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Are you a research staff member working with bioinformatics data? This hands-on training is designed to help you build scalable, reproducible data analysis pipelines using Nextflow. As data volumes grow and analyses become more complex, mastering workflow management tools is essential for ensuring reproducibility and efficiency.
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