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Text Mining in the Context of LLMs

Text mining is the process of extracting meaning, patterns, and trends from unstructured textual data. Massive amounts of unstructured text are prevalent in research. Traditional machine learning algorithms handle only numerical or categorical data. Existing data analytical platforms provide special components to facilitate the analysis of textual data.

This workshop introduces the topic of text mining and provides a tour with hands-on exercises and demonstrations of four text mining tools, each of which supports an interesting and diverse set of features.

Important Note: Registration closes on November 5, 2025.
Registration opens soon – stay tuned for the link!

REDCap Series

What is REDCap?

REDCap is a web-based data capture tool used to create, manage, and deploy research databases and surveys. It has built-in functionalities for data importing and exporting, quality checking, reporting, and basic statistics summarization.

This course will include an overview of the REDCap tool, a demonstration of core features, and hands-on exercises. This course is delivered in 4 parts, 1 hour each.

  • November 10, 2025 – Session 1: Introduction to REDCap Forms. This session provides an overview of the lifecycle of a REDCap project and introduces the basics of a REDCap form.
    Registration closes on November 3, 2025.
  • November 13, 2025 – Session 2: REDCap Branching Logic and Data Piping. This session focuses on how to write the logic to conditionally show and hide parts of a form and how to use the data piping feature to customize questions by displaying previously collected data in their wording.
    Registration closes on November 6, 2025.
  • November 17, 2025 – Session 3: REDCap Longitudinal Studies. This session describes how to utilize the repeatable instruments and events features to set up REDCap projects that require multiple follow-ups over time.
    Registration closes on November 10, 2025.
  • November 18, 2025 – Session 4: REDCap Surveys. This session covers how to set up REDCap surveys with automated invitations for follow-ups.
    Registration closes on November 11, 2025.

Registration for each session to close one week prior.

Registration opens soon – stay tuned for the link!

Data Preparation

This course provides you with essential knowledge and skills to effectively prepare data for analysis. Starting with an overview of the Data Analytics pipeline and processes, the course explores various statistical and visualization techniques used in Exploratory and Descriptive Analytics to understand historical data. You will then delve into the art of Data Preparation, gaining expertise in data cleaning, handling missing values, detecting and handling outliers, as well as transforming and engineering features.

By the end of the course, you will be equipped with the necessary tools to ensure data quality and integrity, enabling you to make informed decisions and derive valuable insights from their data.

Important Note: Registration closes on October 28, 2025.
Registration opens soon – stay tuned for the link!

Introduction to Parallel Programming

Introduction to Parallel Programming with Python using MPI

Parallel programming is key in High Performance Computing. It allows us to run big jobs in a timely manner and leverage a cluster’s resources. In this workshop, you will learn about parallelization, how to write parallel programs, and run them on a parallel system. MPI (Message Passing Interface) will be used in combination with Python.

Important Note: Registration closes on October 27, 2025.
Registration opens soon – stay tuned for the link!

Introduction to Python

This course is designed to provide you with a solid foundation in Python programming language. Through a comprehensive curriculum and hands-on coding exercises, you will learn the fundamentals of Python syntax, data types, functions, and working with data.

By the end of the course, you will have gained the essential skills to write Python programs, solve problems, and build the foundation for more advanced Python development. Whether you are a beginner or have some programming experience, this course will equip you with the necessary tools to start your journey in Python programming.

Important Note: Registration closes on October 23, 2025.
Registration opens soon – stay tuned for the link!

Introduction to Bioinformatics

This introductory course offers you a comprehensive introduction to the field of bioinformatics and its applications in analyzing biological big data. You will gain experience utilizing bioinformatics tools and techniques within an HPC environment, including the CAC’s HPC platform, Frontenac, and the other resources available throughout the national compute ecosystem of the Digital Research Alliance of Canada.

By the end of the course, you will have the necessary skills to effectively navigate and analyze biological data using bioinformatics approaches, enabling you to uncover meaningful insights and contribute to advancements in the field of life sciences.

Important Note: Registration closes on October 20, 2025.
Registration opens soon – stay tuned for the link!

Introduction to Linux

This course provides you with a foundational understanding of the Linux command line interface. Through a combination of theoretical knowledge and hands-on practical exercises, you will learn essential concepts such as file navigation, command-line operations, file permissions, text editing, and basic scripting.

By the end of the course, you will have the necessary skills to confidently work in a Linux environment and leverage its power for various computing tasks.

Important Note: Registration closes on October 16, 2025.
Registration opens soon – stay tuned for the link!

Introduction to High-Performance Computing (HPC)

High-Performance Computing (using Frontenac)

This course offers a comprehensive introduction to the CAC’s high-performance computing (HPC) platform, Frontenac, as well as other resources within the national compute ecosystem of the Digital Research Alliance of Canada.

By the end of the workshop, you will know how to connect to the cluster, submit and manage jobs using a scheduler, transfer files, and access software through environment modules.

This course will also cover new features in the Frontenac cluster, including the availability of interactive applications such as JupyterLab and RStudio. Additionally, the session will discuss the different types of GPUs available and how to access them on Frontenac.

Important Note: Registration closes on October 15, 2025.
Registration opens soon – stay tuned for the link!

Building Campus Strategies for Coordinated Data Support

CAC joins Queen's in new project dedicated to coordinated data support services

Researchers are producing unprecedented amounts of data and data intensive research is growing rapidly across disciplines. Research data support services offered at universities are often siloed, which can cause inefficient duplication of services and significant gaps in programming and support. As a result, there is a need to develop a strategic, unified approach to providing data support services to ensure researchers have access to the tools and resources they need.

To address these challenges, we are pleased to announce that the Centre for Advanced Computing at Queen’s University is amongst the institutional partners participating in Ithaka S+R’s initiative, “Building Campus Strategies for Coordinated Data Support,” a cohort-based project with 29 universities across Canada and the US. This two-year initiative will support the Queen’s research community through several deliverables that aim to ensure the future viability of research data support services in the following ways:

  • Catalogue and analyze the research data services currently offered locally 
  • Investigate the experiences of faculty and students in navigating and accessing existing research data services at Queen’s and identify current barriers and gaps 
  • Build tools to assist researchers in navigating existing research data services 
  • Develop strategic plans for better coordination of current and future services 

In addition, the project will contribute to developing an international benchmarking dataset on current data support services, which will in turn inform our own strategic planning processes. This project aligns with the University’s Strategic Goals to inspire research excellence and advance social impact and sustainability; enhance research and teaching integration; and strengthen the University’s impact on a global scale.

Watch for project updates on progress and for an invitation to members of the Queen’s community participate in interviews to help the implementation committee better understand researcher experiences with current research data services and identify additional support requirements.

We are delighted to have assembled a project team and steering committee with stakeholders from across the University. We would like to thank the Queen’s University Library for funding this initiative.

For questions about the project, please reach out to rdm.library@queensu.ca.

Project team members include

Meghan Goodchild, Principal Investigator (Queen’s University Library) 

Alexandra Cooper (Queen’s University Library) 

Elise Degen (Centre for Advanced Computing) 

Rebecca Pero (Vice-Principal Research Portfolio) 

Nevil Silverius (Centre for Advanced Computing) 

Steering committee members include

Mark Asberg (Vice-Provost and University Librarian)

Sandra Morden, Head of Digital Initiatives and Open Scholarship, Queen’s University Library

Betsy Donald (Associate Vice-Principal Research)

Nicole Hunniford (Executive Director, Finance & Administration, Vice-Principal Research / Interim Director, Advanced Research Computing)

Kent Novakowski (Associate Vice-Principal Research)

About Ithaka S+R

Ithaka S+R is a non-profit organization that offers research and consulting services to libraries, publishers, scholarly societies, universities, and other non-profit organizations, and produces public research reports to advance research and teaching in sustainable ways.