{"id":7761,"date":"2026-01-12T14:48:25","date_gmt":"2026-01-12T19:48:25","guid":{"rendered":"https:\/\/www.calculquebec.ca\/?page_id=7761"},"modified":"2026-01-15T10:28:58","modified_gmt":"2026-01-15T15:28:58","slug":"catalog","status":"publish","type":"page","link":"https:\/\/www.calculquebec.ca\/en\/academic-research-services\/training\/catalog\/","title":{"rendered":"Training Catalog"},"content":{"rendered":"

<\/p>\n

\n

Welcome to our training catalog dedicated to the research community! Check our Eventbrite page<\/a> for upcoming dates. Most of our workshops are available in the fall and winter<\/strong>. Some of them are also integrated into certain streams of our Spring School<\/strong>. If you have any questions or comments, please write to us. We will be happy to answer you.<\/p>\n

<\/p>\n

\n
Explore our Eventbrite page <\/strong>\"external<\/a><\/span><\/div>\n
Contact us <\/strong>\"external<\/a><\/span><\/div>\n<\/p><\/div>\n<\/div>\n

<\/p>\n

<\/div>\n

Fundamentals of Digital Research<\/strong><\/h2>\n
\n

Acquiring digital skills is essential for conducting research. These workshops will teach you how to interact with a Linux-based cluster<\/strong> or program in a popular language<\/strong>.<\/p>\n

<\/p>\n

<\/div>\n
\n\n Introduction to the Linux Command Line<\/strong> (LNX101)<\/span>
\n \"Ouvrir\/Fermer\"
\n <\/summary>\n
\n <\/p>\n

Use the command line effectively, an essential tool for advanced computational analysis, such as high-performance computing!<\/strong><\/p>\n

<\/p>\n

\n <\/p>\n
\n \"Duration\"
\n 3 hours<\/span>\n <\/div>\n

<\/p>\n

\n \"Language\"
\n English or French<\/span>\n <\/div>\n

<\/p>\n

\n \"Source\"
\n Open-source tool<\/span>\n <\/div>\n

<\/p>\n

\n \"Level\"
\n No prerequisites<\/span>\n <\/div>\n<\/p><\/div>\n

<\/p>\n

\n <\/p>\n
\n
\n Workshop Description<\/span>\n <\/div>\n
\n

Are you looking to use a terminal on your computer or to work with a supercomputer? Does the command prompt intimidate you? In this workshop, learn the basic commands to manage your files and navigate your folders.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

<\/p>\n

\n
\n Workshop Plan<\/span>\n <\/div>\n
\n
    \n
  1. Introduction to the command line<\/li>\n
  2. File trees and directories<\/li>\n
  3. File and directory creation, deletion and management<\/li>\n
  4. Command combinations, redirection and filters<\/li>\n
  5. Loops, bash scripts and search<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

    \n <\/div>\n<\/details>\n

    <\/p>\n

    \n\n Introduction to Programming with R<\/strong> (R101)<\/span>
    \n \"Ouvrir\/Fermer\"
    \n <\/summary>\n
    \n <\/p>\n

    Learn the basics of programming with R to analyze your research data!<\/strong><\/p>\n

    <\/p>\n

    \n <\/p>\n
    \n \"Duration\"
    \n 3 hours<\/span>\n <\/div>\n

    <\/p>\n

    \n \"Language\"
    \n in French Only<\/span>\n <\/div>\n

    <\/p>\n

    \n \"Source\"
    \n Free and open source language<\/span>\n <\/div>\n

    <\/p>\n

    \n \"Level\"
    \n No prerequisites<\/span>\n <\/div>\n<\/p><\/div>\n

    <\/p>\n

    \n <\/p>\n
    \n
    \n Workshop Description<\/span>\n <\/div>\n
    \n

    You\u2019ve never programmed before but would like to automate your data processing? Discover the fundamental concepts of programming through the R language. Also learn how to manipulate data, create simple charts, and automate repetitive tasks.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

    <\/p>\n

    \n
    \n Workshop Plan<\/span>\n <\/div>\n
    \n
      \n
    1. Basics of the R language<\/li>\n
    2. Data analysis and visualization<\/li>\n
    3. Lists, repeated operations, conditional expressions, and functions<\/li>\n
    4. The R environment on supercomputers<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

      \n <\/div>\n<\/details>\n

      <\/p>\n

      <\/div>\n
      \n\n Introduction to Programming with Python<\/strong> (PYT101)<\/span>
      \n \"Ouvrir\/Fermer\"
      \n <\/summary>\n
      \n <\/p>\n

      Get started with programming in Python, the most popular language in data science!<\/strong><\/p>\n

      <\/p>\n

      \n <\/p>\n
      \n \"Duration\"
      \n 3 hours<\/span>\n <\/div>\n

      <\/p>\n

      \n \"Language\"
      \n English or French<\/span>\n <\/div>\n

      <\/p>\n

      \n \"Source\"
      \n Free and open source language<\/span>\n <\/div>\n

      <\/p>\n

      \n \"Level\"
      \n No prerequisites<\/span>\n <\/div>\n<\/p><\/div>\n

      <\/p>\n

      \n <\/p>\n
      \n
      \n Workshop Description<\/span>\n <\/div>\n
      \n

      Looking to get into programming? Python is an accessible and versatile language that offers powerful analytical capabilities. In this workshop, you’ll learn the fundamental concepts that will enable you to create your first scripts.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

      <\/p>\n

      \n
      \n Workshop Plan<\/span>\n <\/div>\n
      \n
        \n
      1. Mathematical operations<\/li>\n
      2. Data types (strings, integers, booleans, lists, dictionaries)<\/li>\n
      3. Scripting<\/li>\n
      4. Importing packages<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

        <\/p>\n

        \n

        <\/p>\n

        \n \"opening\n <\/div>\n

        <\/p>\n

        \n

        A very good introduction for a 3-hour workshop, it will get you started on the right track with Python.<\/p>\n

        Mohammed, bioinformatics intern at the University of Montreal<\/p>\n<\/p><\/div>\n

        <\/p>\n

        \n \"closing\n <\/div>\n<\/p><\/div>\n

        \n <\/div>\n<\/details>\n

        <\/p>\n

        <\/div>\n
        \n\n Enhancing your Python Programming Skills<\/strong> (PYT102)<\/span>
        \n \"Ouvrir\/Fermer\"
        \n <\/summary>\n
        \n <\/p>\n

        Discover the best techniques to structure, automate, and accelerate your analyses!<\/strong><\/p>\n

        <\/p>\n

        \n <\/p>\n
        \n \"Duration\"
        \n 3 hours<\/span>\n <\/div>\n

        <\/p>\n

        \n \"Language\"
        \n English or French<\/span>\n <\/div>\n

        <\/p>\n

        \n \"Source\"
        \n Free and open source language<\/span>\n <\/div>\n

        <\/p>\n

        \n \"Level\"
        \n Prerequisites: Introduction to Programming with Python (PYT101)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

        <\/p>\n

        \n <\/p>\n
        \n
        \n Workshop Description<\/span>\n <\/div>\n
        \n

        Do you already know the basics of Python and want to take the next step? This workshop will teach you how to structure your scripts for more complex and reusable analyses. You’ll learn to automate your processing with loops and conditionals, parse data files, and organize your code with functions and classes.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

        <\/p>\n

        \n
        \n Workshop Plan<\/span>\n <\/div>\n
        \n
          \n
        1. for<\/em> loops<\/li>\n
        2. if<\/em> statements<\/li>\n
        3. Reading files<\/li>\n
        4. Functions<\/li>\n
        5. Classes<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

          <\/p>\n

          \n

          <\/p>\n

          \n \"opening\n <\/div>\n

          <\/p>\n

          \n

          The Python course was an extremely valuable experience. The instructor explained the concepts clearly and practically, and the exercises helped me solidify my understanding. I highly recommend this course to anyone interested in programming.<\/p>\n

          Sanaz, master\u2019s student in computer science<\/p>\n<\/p><\/div>\n

          <\/p>\n

          \n \"closing\n <\/div>\n<\/p><\/div>\n

          \n <\/div>\n<\/details>\n

          <\/p>\n

          <\/div>\n

          Research Data Management<\/strong><\/h2>\n
          \n

          Good organization strengthens the integrity of your projects. Learn how to structure your workflow with data management methods and tools<\/strong>.<\/p>\n

          <\/p>\n

          \n\n Data Exploration and Cleaning with OpenRefine<\/strong> (DAT101)<\/span>
          \n \"Ouvrir\/Fermer\"
          \n <\/summary>\n
          \n <\/p>\n

          Organize your data without programming, with OpenRefine!<\/strong><\/p>\n

          <\/p>\n

          \n <\/p>\n
          \n \"Duration\"
          \n 3 hours<\/span>\n <\/div>\n

          <\/p>\n

          \n \"Language\"
          \n French only<\/span>\n <\/div>\n

          <\/p>\n

          \n \"Source\"
          \n Open-source tool<\/span>\n <\/div>\n

          <\/p>\n

          \n \"Level\"
          \n No prerequisites<\/span>\n <\/div>\n<\/p><\/div>\n

          <\/p>\n

          \n <\/p>\n
          \n
          \n Workshop Description<\/span>\n <\/div>\n
          \n

          Do you spend hours cleaning your data manually? The open-source software OpenRefine allows you to do this efficiently with an intuitive graphical interface. You will learn how to detect typos and standardize formats, while keeping track of all your changes.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

          <\/p>\n

          \n
          \n Workshop Plan<\/span>\n <\/div>\n
          \n
            \n
          1. Filters and facets<\/li>\n
          2. Correcting erroneous data and typos<\/li>\n
          3. Automation of changes<\/li>\n
          4. Data reconciliation and enhancement<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

            \n <\/div>\n<\/details>\n

            <\/p>\n

            \n\n Version Control with Git<\/strong> (GIT101)<\/span>
            \n \"Ouvrir\/Fermer\"
            \n <\/summary>\n
            \n <\/p>\n

            Track the evolution of your projects and collaborate effectively with your team!<\/strong><\/p>\n

            <\/p>\n

            \n <\/p>\n
            \n \"Duration\"
            \n 3 hours<\/span>\n <\/div>\n

            <\/p>\n

            \n \"Language\"
            \n English or French<\/span>\n <\/div>\n

            <\/p>\n

            \n \"Source\"
            \n Open-source tool<\/span>\n <\/div>\n

            <\/p>\n

            \n \"Level\"
            \n No prerequisites<\/span>\n <\/div>\n<\/p><\/div>\n

            <\/p>\n

            \n <\/p>\n
            \n
            \n Workshop Description<\/span>\n <\/div>\n
            \n

            Have you ever lost important code or had trouble collaborating on a project? Git solves these problems by keeping a complete history of your work. This workshop teaches you the basics to save your progress, go back in case of an error, and work in a team.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

            <\/p>\n

            \n
            \n Workshop Plan<\/span>\n <\/div>\n
            \n
              \n
            1. Git configuration<\/li>\n
            2. Repository creation<\/li>\n
            3. Version tracking and exploring version history<\/li>\n
            4. Remote repositories and working with others<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

              \n <\/div>\n<\/details>\n

              <\/p>\n

              \n\n Research Data Management and Sensitive Data<\/strong> (GDR101)<\/span>
              \n \"Ouvrir\/Fermer\"
              \n <\/summary>\n
              \n <\/p>\n

              Transform your data management with effective and responsible practices!<\/strong><\/p>\n

              <\/p>\n

              \n <\/p>\n
              \n \"Duration\"
              \n 3 hours<\/span>\n <\/div>\n

              <\/p>\n

              \n \"Language\"
              \n English or French<\/span>\n <\/div>\n

              <\/p>\n

              \n \"Level\"
              \n No prerequisites<\/span>\n <\/div>\n<\/p><\/div>\n

              <\/p>\n

              \n <\/p>\n
              \n
              \n Workshop Description<\/span>\n <\/div>\n
              \n

              Are you wasting valuable time searching for your own data? This workshop guides you through the challenges of research data management. Discover best practices and concepts related to sensitive data. Leave with new knowledge to manage, protect, and leverage your data throughout its lifecycle.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

              <\/p>\n

              \n
              \n Workshop Plan<\/span>\n <\/div>\n
              \n
                \n
              1. Data and metadata<\/li>\n
              2. Data lifecycle<\/li>\n
              3. FAIR principles and best management practices<\/li>\n
              4. Classification of sensitive data<\/li>\n
              5. Anonymization and depersonalization of data<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                \n <\/div>\n<\/details>\n

                <\/p>\n

                <\/div>\n

                High Performance Computing<\/strong><\/h2>\n
                \n

                Using a supercomputer effectively requires specific skills. These progressive workshops guide you from your first analyses<\/strong> to parallelization techniques<\/strong>, including best practices<\/strong> for use.\n<\/p>\n

                <\/p>\n

                <\/div>\n
                \n\n First Steps on Supercomputers<\/strong> (CIP101)<\/span>
                \n \"Ouvrir\/Fermer\"
                \n <\/summary>\n
                \n <\/p>\n

                Connect to a supercomputer and launch your first high-performance computation!<\/strong><\/p>\n

                <\/p>\n

                \n <\/p>\n
                \n \"Duration\"
                \n 3 hours<\/span>\n <\/div>\n

                <\/p>\n

                \n \"Language\"
                \n English or French<\/span>\n <\/div>\n

                <\/p>\n

                \n \"Source\"
                \n Open-source tool (Linux)<\/span>\n <\/div>\n

                <\/p>\n

                \n \"Level\"
                \n Prerequisites: Introduction to the Linux Command Line (LNX101)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                <\/p>\n

                \n <\/p>\n
                \n
                \n Workshop Description<\/span>\n <\/div>\n
                \n

                Is your personal computer showing its limitations for conducting your research? Learn how to use a supercomputer and take your analyses to the next level!<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                <\/p>\n

                \n
                \n Workshop Plan<\/span>\n <\/div>\n
                \n
                  \n
                1. Introduction to high performance computing<\/li>\n
                2. File transfer and using software on our clusters<\/li>\n
                3. The job scheduler and job submission<\/li>\n
                4. Common mistakes, best practices and tips<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                  \n <\/div>\n<\/details>\n

                  <\/p>\n

                  \n\n JupyterLab on Supercomputers<\/strong> (LAB101)<\/span>
                  \n \"Ouvrir\/Fermer\"
                  \n <\/summary>\n
                  \n <\/p>\n

                  Analyze your data with a graphical interface!<\/strong><\/p>\n

                  <\/p>\n

                  \n <\/p>\n
                  \n \"Duration\"
                  \n 2 hours<\/span>\n <\/div>\n

                  <\/p>\n

                  \n \"Language\"
                  \n English or French<\/span>\n <\/div>\n

                  <\/p>\n

                  \n \"Source\"
                  \n Open-source tool<\/span>\n <\/div>\n

                  <\/p>\n

                  \n \"Level\"
                  \n No prerequisites<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                  <\/p>\n

                  \n <\/p>\n
                  \n
                  \n Workshop Description<\/span>\n <\/div>\n
                  \n

                  Do you need an overview of your work? JupyterLab is an interactive tool that gives you access to a graphical and intuitive interface. Learn how to create notebooks (combining code, text, and visualizations) and access tools like R Studio, VS Code, or OpenRefine.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                  <\/p>\n

                  \n
                  \n Workshop Plan<\/span>\n <\/div>\n
                  \n
                    \n
                  1. Introduction to JupyterLab<\/li>\n
                  2. Best practices<\/li>\n
                  3. Notebooks (Python, R, Julia)<\/li>\n
                  4. Virtual Desktop, VS Code, OpenRefine, LibreQDA<\/li>\n
                  5. Resource Monitoring<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                    \n <\/div>\n<\/details>\n

                    <\/p>\n

                    <\/div>\n
                    \n\n Using Compute Clusters Effectively<\/strong> (CIP102)<\/span>
                    \n \"Ouvrir\/Fermer\"
                    \n <\/summary>\n
                    \n <\/p>\n

                    Identify and correct inefficient tasks on Narval and Rorqual using their portal!<\/strong><\/p>\n

                    <\/p>\n

                    \n <\/p>\n
                    \n \"Duration\"
                    \n 3 hours<\/span>\n <\/div>\n

                    <\/p>\n

                    \n \"Language\"
                    \n French only<\/span>\n <\/div>\n

                    <\/p>\n

                    \n \"Source\"
                    \n Open-source tool (Linux)<\/span>\n <\/div>\n

                    <\/p>\n

                    \n \"Level\"
                    \n Prerequisites: First Steps on Supercomputers (CIP101)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                    <\/p>\n

                    \n <\/p>\n
                    \n
                    \n Workshop Description<\/span>\n <\/div>\n
                    \n

                    Do your jobs run slowly or consume too many resources? This workshop will teach you about CPU, GPU, and memory usage on the Narval and Rorqual clusters. You’ll learn about common mistakes that lower your priority and techniques for maximizing your performance using portals.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                    <\/p>\n

                    \n
                    \n Workshop Plan<\/span>\n <\/div>\n
                    \n
                      \n
                    1. Priority concept<\/li>\n
                    2. Use of portals<\/li>\n
                    3. Waste of resources<\/li>\n
                    4. SBATCH submission commands<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                      \n <\/div>\n<\/details>\n

                      <\/p>\n

                      \n\n Job Monitoring and Resource Estimation<\/strong> (CIP201)<\/span>
                      \n \"Ouvrir\/Fermer\"
                      \n <\/summary>\n
                      \n <\/p>\n

                      Determine the necessary resources for your computations and how to monitor them!<\/strong><\/p>\n

                      <\/p>\n

                      \n <\/p>\n
                      \n \"Duration\"
                      \n 3 hours<\/span>\n <\/div>\n

                      <\/p>\n

                      \n \"Language\"
                      \n English or French<\/span>\n <\/div>\n

                      <\/p>\n

                      \n \"Source\"
                      \n Open-source tool (Linux)<\/span>\n <\/div>\n

                      <\/p>\n

                      \n \"Level\"
                      \n Prerequisites: First Steps on Supercomputers (CIP101)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                      <\/p>\n

                      \n <\/p>\n
                      \n
                      \n Workshop Description<\/span>\n <\/div>\n
                      \n

                      How many processors, how much memory, and how much time should you request for your compute job? A poor estimate can cause your jobs to fail or lower your future priority. This workshop gives you the tools to evaluate your actual needs and track the resources consumed.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                      <\/p>\n

                      \n
                      \n Workshop Plan<\/span>\n <\/div>\n
                      \n
                        \n
                      1. Understanding the various job types<\/li>\n
                      2. Choosing the right resources<\/li>\n
                      3. Monitoring active and completed jobs<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                        <\/p>\n

                        \n

                        <\/p>\n

                        \n \"opening\n <\/div>\n

                        <\/p>\n

                        \n

                        Good introductory course for beginners to clusters.<\/p>\n

                        Youjia Li, Phd Student at McGill University<\/p>\n<\/p><\/div>\n

                        <\/p>\n

                        \n \"closing\n <\/div>\n<\/p><\/div>\n

                        \n <\/div>\n<\/details>\n

                        <\/p>\n

                        \n\n Managing Large Batches of Jobs<\/strong> (CIP202)<\/span>
                        \n \"Ouvrir\/Fermer\"
                        \n <\/summary>\n
                        \n <\/p>\n

                        Efficiently manage the execution of numerous computations on supercomputers!<\/strong><\/p>\n

                        <\/p>\n

                        \n <\/p>\n
                        \n \"Duration\"
                        \n 3 hours<\/span>\n <\/div>\n

                        <\/p>\n

                        \n \"Language\"
                        \n English or French<\/span>\n <\/div>\n

                        <\/p>\n

                        \n \"Source\"
                        \n Open-source tool (Linux)<\/span>\n <\/div>\n

                        <\/p>\n

                        \n \"Level\"
                        \n Prerequisites: First Steps on Supercomputers (CIP101)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                        <\/p>\n

                        \n <\/p>\n
                        \n
                        \n Workshop Description<\/span>\n <\/div>\n
                        \n

                        Need to run hundreds of variations of your analysis? Do you need to repeat the same computation with different datasets? This workshop shows you how to structure and submit numerous jobs without overwhelming the scheduler. You’ll learn grouping and parallelization techniques to launch your analyses.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                        <\/p>\n

                        \n
                        \n Workshop Plan<\/span>\n <\/div>\n
                        \n
                          \n
                        1. Introduction to data parallelism<\/li>\n
                        2. Job arrays<\/li>\n
                        3. Parameter sweeps with GNU Parallel<\/li>\n
                        4. META-Farm and GLOST tools<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                          <\/p>\n

                          \n

                          <\/p>\n

                          \n \"opening\n <\/div>\n

                          <\/p>\n

                          \n

                          They are very good, especially the documentation provided so that we can go back and review things ourselves.<\/p>\n

                          Mariana, researcher at \u00c9TS<\/p>\n<\/p><\/div>\n

                          <\/p>\n

                          \n \"closing\n <\/div>\n<\/p><\/div>\n

                          \n <\/div>\n<\/details>\n

                          <\/p>\n

                          <\/div>\n

                          CPU and GPU Resources<\/strong><\/h2>\n
                          \n

                          CPUs and GPUs are two types of processors used to perform calculations. Learn how to choose the right resource<\/strong> for your needs, speed up your Python code<\/strong> on these processors, or optimize GPU usage<\/strong>.<\/p>\n

                          <\/p>\n

                          <\/div>\n
                          \n\n CPU vs GPU Strategies in Python<\/strong> (CGPU101)<\/span>
                          \n \"Ouvrir\/Fermer\"
                          \n <\/summary>\n
                          \n <\/p>\n

                          Make smart choices about when to use your CPUs and GPUs to get the most out of them!<\/strong><\/p>\n

                          <\/p>\n

                          \n <\/p>\n
                          \n \"Duration\"
                          \n 3 hours<\/span>\n <\/div>\n

                          <\/p>\n

                          \n \"Language\"
                          \n English or French<\/span>\n <\/div>\n

                          <\/p>\n

                          \n \"Source\"
                          \n Free and open source language<\/span>\n <\/div>\n

                          <\/p>\n

                          \n \"Level\"
                          \n Prerequisites: First Steps on Supercomputers (CIP101)<\/a> and Introduction to Programming with Python (PYT101)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                          <\/p>\n

                          \n <\/p>\n
                          \n
                          \n Workshop Description<\/span>\n <\/div>\n
                          \n

                          When should you use a GPU instead of a CPU for your computations? This workshop will help you identify when GPUs provide a real advantage and when they’re unnecessary. You’ll discover best practices for efficiently utilizing these expensive resources and avoiding waste.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                          <\/p>\n

                          \n
                          \n Workshop Plan<\/span>\n <\/div>\n
                          \n
                            \n
                          1. CPU vs GPU: Overview<\/li>\n
                          2. Monitoring tools<\/li>\n
                          3. Code profiling tools<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                            \n <\/div>\n<\/details>\n

                            <\/p>\n

                            \n\n Python Code Acceleration with Numba<\/strong> (PYT301)<\/span>
                            \n \"Ouvrir\/Fermer\"
                            \n <\/summary>\n
                            \n <\/p>\n

                            Accelerate your Python functions on CPU and GPU using Numba!<\/strong><\/p>\n

                            <\/p>\n

                            \n <\/p>\n
                            \n \"Duration\"
                            \n 3 hours<\/span>\n <\/div>\n

                            <\/p>\n

                            \n \"Language\"
                            \n English only<\/span>\n <\/div>\n

                            <\/p>\n

                            \n \"Source\"
                            \n Free and open source language<\/span>\n <\/div>\n

                            <\/p>\n

                            \n \"Level\"
                            \n Prerequisites: Enhancing your Python Programming Skills (PYT102)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                            <\/p>\n

                            \n <\/p>\n
                            \n
                            \n Workshop Description<\/span>\n <\/div>\n
                            \n

                            Python is easy to use, but sometimes too slow for your intensive computations? The Numba compiler automatically translates your Python code to make it faster, whether on CPU or GPU. This workshop teaches you the essential techniques to optimize your most time-consuming functions, all while benefiting from the simplicity of Python.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                            <\/p>\n

                            \n
                            \n Workshop Plan<\/span>\n <\/div>\n
                            \n
                              \n
                            1. Why use GPUs for computing?<\/li>\n
                            2. Understanding difference between CPU and GPU<\/li>\n
                            3. Numba: just-in-time compilation<\/li>\n
                            4. Parallel computing: distributing workload among CPU and GPU cores<\/li>\n
                            5. Numba + CUDA: porting a CPU code to GPU<\/li>\n
                            6. Numba + CUDA: more acceleration with shared memory, streams<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                              \n <\/div>\n<\/details>\n

                              <\/p>\n

                              \n\n Maximizing GPU Usage with MIGs, MPS, and Time-Slicing<\/strong> (CIP203)<\/span>
                              \n \"Ouvrir\/Fermer\"
                              \n <\/summary>\n
                              \n <\/p>\n

                              Divide your GPUs to multiply your productivity!<\/strong><\/p>\n

                              <\/p>\n

                              \n <\/p>\n
                              \n \"Duration\"
                              \n 3 hours<\/span>\n <\/div>\n

                              <\/p>\n

                              \n \"Language\"
                              \n English only<\/span>\n <\/div>\n

                              <\/p>\n

                              \n \"Level\"
                              \n Prerequisites: experience in performing tasks on GPUs and Using Compute Clusters Effectively (CIP102)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                              <\/p>\n

                              \n <\/p>\n
                              \n
                              \n Workshop Description<\/span>\n <\/div>\n
                              \n

                              Want to unlock the full potential of your GPU resources? Learn resource-sharing techniques to transform how you use your GPUs. Maximize your computational efficiency through the use of fractional GPUs or by sharing resources between multiple jobs and tasks. This hands-on workshop is particularly essential for users of powerful H100 systems, as poor GPU utilization leads to wasted resources, lower job priority, and potential job termination.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                              <\/p>\n

                              \n
                              \n Workshop Plan<\/span>\n <\/div>\n
                              \n
                                \n
                              1. Why bother maximizing GPU usage<\/li>\n
                              2. How to waste GPU cycles<\/li>\n
                              3. CUDA streams<\/li>\n
                              4. Wasting less GPU resources with the MIGs<\/li>\n
                              5. Sharing one GPU between multiple tasks with the MPS<\/li>\n
                              6. TimeSlicing<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                                \n <\/div>\n<\/details>\n

                                <\/p>\n

                                <\/div>\n

                                Data Analysis and Visualization<\/strong><\/h2>\n
                                \n

                                The processing of large data sets is at the heart of many research projects. These additional training courses will enable you to automate your analyses<\/strong> and produce powerful visualizations<\/strong>, from data structured in tabular form.<\/p>\n

                                <\/p>\n

                                <\/div>\n
                                \n\n Data Analysis with Python<\/strong> (DAT201)<\/span>
                                \n \"Ouvrir\/Fermer\"
                                \n <\/summary>\n
                                \n <\/p>\n

                                Load and analyze tabular data with Python tools!<\/strong><\/p>\n

                                <\/p>\n

                                \n <\/p>\n
                                \n \"Duration\"
                                \n 3 hours<\/span>\n <\/div>\n

                                <\/p>\n

                                \n \"Language\"
                                \n English or French<\/span>\n <\/div>\n

                                <\/p>\n

                                \n \"Source\"
                                \n Free and open source language<\/span>\n <\/div>\n

                                <\/p>\n

                                \n \"Level\"
                                \n Prerequisites: Introduction to Programming with Python (PYT101)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                                <\/p>\n

                                \n <\/p>\n
                                \n
                                \n Workshop Description<\/span>\n <\/div>\n
                                \n

                                Got files with thousands of rows that are a pain to handle in Excel? It’s time to automate your data analysis with Python and its Pandas library! This workshop will guide you through loading, cleaning, and analyzing large datasets in table format.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                                <\/p>\n

                                \n
                                \n Workshop Plan<\/span>\n <\/div>\n
                                \n
                                  \n
                                1. Pandas and DataFrames (data tables) in Python<\/li>\n
                                2. Descriptive statistics and data grouping<\/li>\n
                                3. Selecting data rows and columns<\/li>\n
                                4. Cleaning undefined data<\/li>\n
                                5. Combining datasets<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                                  <\/p>\n

                                  \n

                                  <\/p>\n

                                  \n \"opening\n <\/div>\n

                                  <\/p>\n

                                  \n

                                  Good course, gives a good introduction to data analysis with Python, well-organized and presented.<\/p>\n

                                  Mohammed, intern in a bioinformatics research group at the University of Montreal<\/p>\n<\/p><\/div>\n

                                  <\/p>\n

                                  \n \"closing\n <\/div>\n<\/p><\/div>\n

                                  \n <\/div>\n<\/details>\n

                                  <\/p>\n

                                  <\/div>\n
                                  \n\n Data Visualization with Python<\/strong> (DAT203)<\/span>
                                  \n \"Ouvrir\/Fermer\"
                                  \n <\/summary>\n
                                  \n <\/p>\n

                                  Transform your data into compelling visualizations!<\/strong><\/p>\n

                                  <\/p>\n

                                  \n <\/p>\n
                                  \n \"Duration\"
                                  \n 3 hours<\/span>\n <\/div>\n

                                  <\/p>\n

                                  \n \"Language\"
                                  \n English or French<\/span>\n <\/div>\n

                                  <\/p>\n

                                  \n \"Source\"
                                  \n Free and open source language<\/span>\n <\/div>\n

                                  <\/p>\n

                                  \n \"Level\"
                                  \n Prerequisites: Data Analysis with Python (DAT201)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                                  <\/p>\n

                                  \n <\/p>\n
                                  \n
                                  \n Workshop Description<\/span>\n <\/div>\n
                                  \n

                                  How can you uncover the hidden trends in your thousands of data rows? This workshop teaches you how to create interactive charts from your tabular data. You’ll master histograms, time series plots, distributions, and multi-faceted graphs to transform your tables into impactful visualizations.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                                  <\/p>\n

                                  \n
                                  \n Workshop Plan<\/span>\n <\/div>\n
                                  \n
                                    \n
                                  1. Simple visualizations from a DataFrame<\/li>\n
                                  2. Creating interactive charts with Altair<\/li>\n
                                  3. Building a figure step-by-step using a grammar of graphics<\/li>\n
                                  4. Visualizing time series and data distributions<\/li>\n
                                  5. Creating multiple facets in a single figure<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                                    <\/p>\n

                                    \n

                                    <\/p>\n

                                    \n \"opening\n <\/div>\n

                                    <\/p>\n

                                    \n

                                    Now I learned how to create graphics on Python, even if I’m a beginner – Excellent workshop!<\/p>\n

                                    Fares Dhane, data analyst<\/p>\n<\/p><\/div>\n

                                    <\/p>\n

                                    \n \"closing\n <\/div>\n<\/p><\/div>\n

                                    \n <\/div>\n<\/details>\n

                                    <\/p>\n

                                    <\/div>\n

                                    Artificial Intelligence<\/strong><\/h2>\n
                                    \n

                                    Artificial intelligence enables a computer to detect trends from large amounts of data. These trainings will guide you from the creation of predictive models<\/strong> to the training of neural networks<\/strong>.<\/p>\n

                                    <\/p>\n

                                    <\/div>\n
                                    \n\n Machine Learning with Scikit-learn<\/strong> (IA101)<\/span>
                                    \n \"Ouvrir\/Fermer\"
                                    \n <\/summary>\n
                                    \n <\/p>\n

                                    Create predictive models with an accessible AI library!<\/strong><\/p>\n

                                    <\/p>\n

                                    \n <\/p>\n
                                    \n \"Duration\"
                                    \n 3 hours<\/span>\n <\/div>\n

                                    <\/p>\n

                                    \n \"Language\"
                                    \n English or French<\/span>\n <\/div>\n

                                    <\/p>\n

                                    \n \"Source\"
                                    \n Free and open source language<\/span>\n <\/div>\n

                                    <\/p>\n

                                    \n \"Level\"
                                    \n Prerequisites: statistics and Data Visualization with Python (DAT203)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                                    <\/p>\n

                                    \n <\/p>\n
                                    \n
                                    \n Workshop Description<\/span>\n <\/div>\n
                                    \n

                                    Do you want to predict trends and automate your analyses? Discover machine learning, an essential component of artificial intelligence. In this workshop, you’ll explore the main methods for classification, prediction, and trend detection. Step by step, you’ll also learn to create your own predictive models with scikit-learn, the go-to Python library in the field.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                                    <\/p>\n

                                    \n
                                    \n Workshop Plan<\/span>\n <\/div>\n
                                    \n
                                      \n
                                    1. A gentle introduction to the mathematics of machine learning<\/li>\n
                                    2. Practical exercises and applications<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                                      \n <\/div>\n<\/details>\n

                                      <\/p>\n

                                      \n\n Deep Learning with PyTorch<\/strong> (IA102)<\/span>
                                      \n \"Ouvrir\/Fermer\"
                                      \n <\/summary>\n
                                      \n <\/p>\n

                                      Create predictive models with a flexible and versatile AI library!<\/strong><\/p>\n

                                      <\/p>\n

                                      \n <\/p>\n
                                      \n \"Duration\"
                                      \n 3 hours<\/span>\n <\/div>\n

                                      <\/p>\n

                                      \n \"Language\"
                                      \n English or French<\/span>\n <\/div>\n

                                      <\/p>\n

                                      \n \"Source\"
                                      \n Free and open source language<\/span>\n <\/div>\n

                                      <\/p>\n

                                      \n \"Level\"
                                      \n Prerequisites: statistics, Data Visualization with Python (DAT203)<\/a>, and Machine Learning with Scikit-learn (IA101)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                                      <\/p>\n

                                      \n <\/p>\n
                                      \n
                                      \n Workshop Description<\/span>\n <\/div>\n
                                      \n

                                      How do ChatGPT, autonomous cars, and image recognition work? Discover the basics of deep learning, a fundamental concept of artificial intelligence. In this workshop, you’ll create neural networks capable of automatically learning from raw data. You’ll also learn to train your own models, using PyTorch, the library used by the largest research labs.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                                      <\/p>\n

                                      \n
                                      \n Workshop Plan<\/span>\n <\/div>\n
                                      \n
                                        \n
                                      1. Review of machine learning with Scikit-learn<\/li>\n
                                      2. Introduction to neural networks<\/li>\n
                                      3. Training neural networks with PyTorch<\/li>\n
                                      4. Introduction to high-performance training<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                                        <\/p>\n

                                        \n

                                        <\/p>\n

                                        \n \"opening\n <\/div>\n

                                        <\/p>\n

                                        \n

                                        Wonderful presentation and speaker! Excellent for beginners in Neural Networks and Deep learning.<\/p>\n

                                        Angela Schlesinger, Data Analyst at the University of Victoria<\/p>\n<\/p><\/div>\n

                                        <\/p>\n

                                        \n \"closing\n <\/div>\n<\/p><\/div>\n

                                        \n <\/div>\n<\/details>\n

                                        <\/p>\n

                                        <\/div>\n

                                        Quantum Computing<\/strong><\/h2>\n
                                        \n

                                        Quantum computing offers new approaches to solving certain complex problems. These training courses will guide you from your first experience with qubits<\/strong> to the design of quantum circuits<\/strong>.<\/p>\n

                                        <\/p>\n

                                        <\/div>\n
                                        \n\n Quantum Computing Theory<\/strong> (CIQ101)<\/span>
                                        \n \"Ouvrir\/Fermer\"
                                        \n <\/summary>\n
                                        \n <\/p>\n

                                        Discover quantum computing by building your own one-qubit simulator!<\/strong><\/p>\n

                                        <\/p>\n

                                        \n <\/p>\n
                                        \n \"Duration\"
                                        \n 2 hours<\/span>\n <\/div>\n

                                        <\/p>\n

                                        \n \"Language\"
                                        \n English or French<\/span>\n <\/div>\n

                                        <\/p>\n

                                        \n \"Source\"
                                        \n Free and open source language<\/span>\n <\/div>\n

                                        <\/p>\n

                                        \n \"Level\"
                                        \n Prerequisites: linear algebra and Data Visualization with Python (DAT203)<\/a> based on these exercises<\/a> \"external<\/span>\n <\/div>\n<\/p><\/div>\n

                                        <\/p>\n

                                        \n <\/p>\n
                                        \n
                                        \n Workshop Description<\/span>\n <\/div>\n
                                        \n

                                        Want to understand how a quantum computer works? This workshop will guide you through the fundamental concepts: qubits, underlying mathematics, and physical systems. You’ll program your first quantum simulator and discover the current challenges of this cutting-edge technology.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                                        <\/p>\n

                                        \n
                                        \n Workshop Plan<\/span>\n <\/div>\n
                                        \n
                                          \n
                                        1. Introducing MonarQ, Calcul Qu\u00e9bec’s quantum computer<\/li>\n
                                        2. Qubit concept<\/li>\n
                                        3. Qubit operations and linear algebra concepts<\/li>\n
                                        4. Quantum state superposition<\/li>\n
                                        5. Development of a one-qubit quantum simulator<\/li>\n
                                        6. Overview of NISQ era constraints<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                                          \n <\/div>\n<\/details>\n

                                          <\/p>\n

                                          \n\n Quantum Programming with PennyLane<\/strong> (CIQ102)<\/span>
                                          \n \"Ouvrir\/Fermer\"
                                          \n <\/summary>\n
                                          \n <\/p>\n

                                          Discover quantum circuits through practical programming exercises in PennyLane!<\/strong><\/p>\n

                                          <\/p>\n

                                          \n <\/p>\n
                                          \n \"Duration\"
                                          \n 2 hours<\/span>\n <\/div>\n

                                          <\/p>\n

                                          \n \"Language\"
                                          \n English or French<\/span>\n <\/div>\n

                                          <\/p>\n

                                          \n \"Source\"
                                          \n Free and open source language<\/span>\n <\/div>\n

                                          <\/p>\n

                                          \n \"Level\"
                                          \n Prerequisites: linear algebra, Data Visualization with Python (DAT203)<\/a>, and Quantum Computing Theory (CIQ101)<\/a><\/span>\n <\/div>\n<\/p><\/div>\n

                                          <\/p>\n

                                          \n <\/p>\n
                                          \n
                                          \n Workshop Description<\/span>\n <\/div>\n
                                          \n

                                          Do you want to program your first quantum circuits? This workshop teaches you quantum programming with PennyLane to create circuits, manipulate quantum gates, perform measurements, and prepare states. You’ll also discover variational circuits for a complete approach to quantum programming.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

                                          <\/p>\n

                                          \n
                                          \n Workshop Plan<\/span>\n <\/div>\n
                                          \n
                                            \n
                                          1. Overview of basic quantum computing concepts<\/li>\n
                                          2. Introduction to quantum circuits with PennyLane<\/li>\n
                                          3. Quantum function, device, qnode<\/li>\n
                                          4. Gates, measurements, and quantum state preparation<\/li>\n
                                          5. Constraints of the NISQ era (circuit depth)<\/li>\n<\/ol><\/div>\n<\/p><\/div>\n<\/p><\/div>\n

                                            <\/p>\n

                                            \n

                                            <\/p>\n

                                            \n \"opening\n <\/div>\n

                                            <\/p>\n

                                            \n

                                            It was great! I learned a lot about the applications of quantum computing and how to begin to implement my own applications.<\/p>\n

                                            Alyson MacKay, PhD student in Chemistry at Concordia University<\/p>\n<\/p><\/div>\n

                                            <\/p>\n

                                            \n \"closing\n <\/div>\n<\/p><\/div>\n

                                            \n <\/div>\n<\/details>\n

                                            \n

                                            The workshop you’re interested in isn’t scheduled? You’d like customized training for your group? Or you simply have a question? Write to us at training@calculquebec.ca<\/a>. You can also check out our partners’ workshops<\/a>.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

                                            Welcome to our training catalog dedicated to the research community! Check our Eventbrite page for upcoming dates. Most of our workshops are available in the fall and winter. Some of them are also integrated into certain streams of our Spring School. If you have any questions or comments, please write to us. We will be…<\/p>\n","protected":false},"author":14,"featured_media":0,"parent":767,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-7761","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.calculquebec.ca\/en\/wp-json\/wp\/v2\/pages\/7761","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.calculquebec.ca\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.calculquebec.ca\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.calculquebec.ca\/en\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/www.calculquebec.ca\/en\/wp-json\/wp\/v2\/comments?post=7761"}],"version-history":[{"count":6,"href":"https:\/\/www.calculquebec.ca\/en\/wp-json\/wp\/v2\/pages\/7761\/revisions"}],"predecessor-version":[{"id":7820,"href":"https:\/\/www.calculquebec.ca\/en\/wp-json\/wp\/v2\/pages\/7761\/revisions\/7820"}],"up":[{"embeddable":true,"href":"https:\/\/www.calculquebec.ca\/en\/wp-json\/wp\/v2\/pages\/767"}],"wp:attachment":[{"href":"https:\/\/www.calculquebec.ca\/en\/wp-json\/wp\/v2\/media?parent=7761"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}