Training Catalog

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.

1. Introduction to the command line
2. File trees and directories
3. File and directory creation, deletion and management
4. Command combinations, redirection and filters
5. Loops, bash scripts and search

You’ve 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.

1. Basics of the R language
2. Data analysis and visualization
3. Lists, repeated operations, conditional expressions, and functions
4. The R environment on supercomputers

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.

1. Mathematical operations
2. Data types (strings, integers, booleans, lists, dictionaries)
3. Scripting
4. Importing packages

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.

1. for loops
2. if statements
3. Reading files
4. Functions
5. Classes

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.

1. Filters and facets
2. Correcting erroneous data and typos
3. Automation of changes
4. Data reconciliation and enhancement

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.

1. Git configuration
2. Repository creation
3. Version tracking and exploring version history
4. Remote repositories and working with others

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.

1. Data and metadata
2. Data lifecycle
3. FAIR principles and best management practices
4. Classification of sensitive data
5. Anonymization and depersonalization of data

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!

1. Introduction to high performance computing
2. File transfer and using software on our clusters
3. The job scheduler and job submission
4. Common mistakes, best practices and tips

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.

1. Introduction to JupyterLab
2. Best practices
3. Notebooks (Python, R, Julia)
4. Virtual Desktop, VS Code, OpenRefine, LibreQDA
5. Resource Monitoring

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.

1. Priority concept
2. Use of portals
3. Waste of resources
4. SBATCH submission commands

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.

1. Understanding the various job types
2. Choosing the right resources
3. Monitoring active and completed jobs

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.

1. Introduction to data parallelism
2. Job arrays
3. Parameter sweeps with GNU Parallel
4. META-Farm and GLOST tools

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.

1. CPU vs GPU: Overview
2. Monitoring tools
3. Code profiling tools

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.

1. Why use GPUs for computing?
2. Understanding difference between CPU and GPU
3. Numba: just-in-time compilation
4. Parallel computing: distributing workload among CPU and GPU cores
5. Numba + CUDA: porting a CPU code to GPU
6. Numba + CUDA: more acceleration with shared memory, streams

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.

1. Why bother maximizing GPU usage
2. How to waste GPU cycles
3. CUDA streams
4. Wasting less GPU resources with the MIGs
5. Sharing one GPU between multiple tasks with the MPS
6. TimeSlicing

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.

1. Pandas and DataFrames (data tables) in Python
2. Descriptive statistics and data grouping
3. Selecting data rows and columns
4. Cleaning undefined data
5. Combining datasets

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.

1. Simple visualizations from a DataFrame
2. Creating interactive charts with Altair
3. Building a figure step-by-step using a grammar of graphics
4. Visualizing time series and data distributions
5. Creating multiple facets in a single figure

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.

1. A gentle introduction to the mathematics of machine learning
2. Practical exercises and applications

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.

1. Review of machine learning with Scikit-learn
2. Introduction to neural networks
3. Training neural networks with PyTorch
4. Introduction to high-performance training

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.

1. Introducing MonarQ, Calcul Québec’s quantum computer
2. Qubit concept
3. Qubit operations and linear algebra concepts
4. Quantum state superposition
5. Development of a one-qubit quantum simulator
6. Overview of NISQ era constraints

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.

1. Overview of basic quantum computing concepts
2. Introduction to quantum circuits with PennyLane
3. Quantum function, device, qnode
4. Gates, measurements, and quantum state preparation
5. Constraints of the NISQ era (circuit depth)