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Presented by Carlos Ramirez Reyes, Ph.D., assistant professor, research data services, University Libraries

This workshop will guide participants through practical techniques for handling messy datasets, including managing missing values, removing duplicates, tidying data and reformatting variables using R. It is ideal for researchers and analysts looking to streamline data preparation for analysis. The session will be a demonstration using R and RStudio. While participants of all skill levels are welcome, this is not an introductory R training. Those already familiar with R and RStudio are encouraged to bring their laptops preloaded with the software if they wish to follow along.

Presented by Alex Knudson M.S., software engineer, Light & Wonder in collaboration with the Â鶹ӳ»­ Bioinformatics Center

This hands-on session will introduce participants to R and RStudio, covering the basics of data import, manipulation and visualization. Ideal for beginners with no prior coding experience.

• Create Basics of R, RStudio and setting up the environment
• Hands-on basics (reading data, simple calculations and navigating R)
• Basic data manipulation and simple visualizations

Curious about AWS cloud computing services or eager to explore their new and exciting tools, like Amazon SageMaker Unified Studio? Join the AWS team for an interactive demo showcasing this powerful tool and its capabilities for accelerating machine learning workflows.

Stay afterward for a relaxed coffee-and-cookie open discussion, where you can ask questions, share challenges from past projects, explore training opportunities, or learn how to begin your cloud computing journey. Everyone is welcome!

Presented by Paul Hurtado, Ph.D., associate professor, mathematics and statistics, Â鶹ӳ»­ in collaboration with Theresa McKim, Ph.D., teaching assistant professor, biology, Â鶹ӳ»­

Learn to turn your data analysis into polished, professional documents! This hands-on workshop covers using R Markdown, Jupyter Notebooks and LaTeX to create dynamic reports, integrate code and visuals, and produce publication-ready outputs.

• Create dynamic reports using R Markdown and Jupyter Notebooks
• Format equations and customize outputs with LaTeX
• Combine code, visualizations, and text for seamless workflows
• Embed R or Python scripts directly into LaTeX documents

Perfect for researchers and students looking to streamline their workflows and enhance the quality of their reports.

Presented by the IBM Team

IBM is hosting an AI Roadmapping and Strategy Workshop to explore the impact of AI on higher education, and provide a forum to explore AI opportunities for the Â鶹ӳ»­. Participants will get the opportunity to explore different AI use cases, provide input on existing challenges and pain points, identify how AI can help to resolve these challenges and outline key resources needed for successful implementation and adoption.

Presented by Jeremy Tiedt, assistant dean, undergraduate student success, College of Business, Â鶹ӳ»­

Presented by Kanishka Manna, Ph.D., postdoctoral scholar, Â鶹ӳ»­ Bioinformatics Center

This hands-on workshop introduces the powerful workflow management system Nextflow for creating automated and reproducible computational pipelines. Participants will gain insight into workflow management systems, explore Nextflow’s advantages, and learn pipeline development through a practical example (not domain specific). This workshop is designed to equip researchers with the skills needed to automate and scale their data analyses efficiently.

No prior experience with Nextflow is required, but familiarity with Unix and basic programming concepts are required.

• Understand how automated pipelines increase reproducibility, consistency and scalability in research
• Learn what Workflow Management Systems (WFMS) are, their key features and why they are essential for efficient research workflows
• Understand the core differences between Nextflow and Snakemake to determine which system best suits your needs
• Install and set up Nextflow and the required tools, including WSL (for Windows), Java and VS Code editor
• Walk through a beginner-friendly Nextflow pipeline, including the “Tacos with Nextflow” example, to understand concepts like processes, channels and configuration syntax
• Learn how Nextflow makes it easy to parallelize tasks and scale your workflows for large datasets
• Understand how to generate useful reports and visualize your workflow as a Directed Acyclic Graph (DAG)

This workshop will emphasize practical learning through hands-on exercises, including a creative and accessible example pipeline to demystify pipeline development.

Presented by Elena Azadbakht, associate professor and health sciences librarian, Teresa Schultz, associate professor and scholarly communication and social sciences librarian and Challen Wright, assistant professor, metadata librarian, Â鶹ӳ»­.

This workshop will provide hands-on learning for participants through the process of preparing and sharing datasets in data repositories to comply with grant funder mandates. Participants will explore various data repositories, including the University’s data repository Dryad, as well as what they will need to do to prepare their data to ensure the data is reusable and understandable and how they can get credit for sharing their data.

Presented by Cassandra Hui, Ph.D., Bioinformatician, Â鶹ӳ»­ Bioinformatics Center

Whether you're new to version control or looking to enhance your project management skills, this hands-on workshop will provide the training you need to leverage GitHub effectively for collaboration and personal use.

Join us for an interactive learning experience where you’ll explore:

• Setting up and navigating GitHub
• Creating and managing repositories for academic projects
• Collaborating on shared repositories

Presented by Alex Knudson, software engineer, Light & Wonder in collaboration with the Â鶹ӳ»­ Bioinformatics Center

Dive deeper into R with this advanced session focusing on data wrangling and visualization using dplyr, tidyr, and ggplot2. Participants will learn practical applications for real-world scenarios.

• Data wrangling with dplyr and tidyr (filtering, grouping, summarizing, reshaping)
• Creating visualizations with ggplot2 (scatterplots, bar charts, customizing themes)
• Applying Tidyverse and ggplot2 in real-world scenarios with guided examples

You’ll leave with practical skills to manage research projects and collaborate seamlessly with others – all while gaining experience with GitHub’s powerful interface. This training will use GitHub online and GitHub Desktop and requires no coding.

Presented by James Ragsdale, doctoral student and instructor, sociology, Â鶹ӳ»­

This interactive workshop examines how researcher decisions — known as researcher degrees of freedom — can unintentionally bias results or inflate type I error rates. It covers cognitive heuristics that may unconsciously lead to questionable research practices. Through group discussions, case studies, and data visualization, participants will explore flexibility in study design, analysis, and reporting while learning strategies to reduce bias and strengthen research integrity.

• Identify key stages in the research process where choices influence outcomes
• Understand the impact of p-hacking, selective reporting, motivated reasoning and HARKing
• Learn strategies to avoid questionable research practices
• Enhance research reliability and credibility through methodological rigor

This workshop is essential for anyone aiming to improve the quality and reproducibility of their research.

Presented by IBM Team

Data is at the core of AI but getting access to datasets for Training, Tuning and Inference is complex and costly (or is it?). IBM’s Global Data Platform powers many large-scale AI implementations including IBM’s own Vela and Blue Vela AI supercomputers. Come learn how data Access, Acceleration, Abstraction and Assurance are fundamental to AI and how IBM has designed large AI clusters to train the Granite family of models.