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Introduction to Python

McMaster University

This beginner level workshop will introduce you to the basic concepts of the world’s most popular Python programming language. You’ll learn to store data in Python data types and variables, as well as learn how to perform operations on numbers and strings. Python IDE Anaconda will be briefly discussed. No prior knowledge of Python is required.

Storage Scores: Store and Back Up Data at McMaster

McMaster University

From very small tabular datasets to mid-size mixed methods records to the titan data for Advanced Research Computing, researchers at McMaster have a wide range of needs for storing research data. But what options are available? What are some workflows when you’re working alone vs with a research team? What’s available if you need a bit more? Join us for a session on research data storage and backup. In this workshop, we’ll start with an overview of different storage platforms available to you as a researcher, their features and drawbacks, and outline data backup and security principles. Then, we’ll share information about the Digital Research Alliance of Canada’s annual Resource Allocation Competition and how researchers can start working with large-scale computational resources. Note: This webinar will be for researchers who are curious about the Resource Allocation Competition but have not accessed it yet. For those who are already accessing it and would like more information, please see the Intermediate High-Performance Computing session with Sergey Mashchenko.

Web Scraping with Python’s Beautiful Soup

McMaster University

This workshop will introduce attendees to techniques for scraping information from the web using Python’s Beautiful Soup (bs4) toolkit. We will begin with a basic overview of the “anatomy” or structure of a webpage. Students will then learn how to write a script for extracting textual data from websites like Reddit and organizing it into spreadsheets. The second half of the workshop will explore how to use Python’s Pandas library to clean and analyze your data. In addition to technical skills, students are encouraged to engage with critical questions like: What is web scraping for and what can we, as researchers, learn from publicly available data? What are the potential ethical and legal challenges of data harvesting, and how do we do it responsibly?

Introduction to/à R

Date: 15 February 2024 R is a free and open-source programming language for statistical computing, modelling, and graphics, with an unbeatable collection of statistical packages. It is extremely popular in […]

Introduction to\à Python

Date: 15 February 2024 In this short session, we will demo some of Python’s capabilities to researchers new to the language, starting with multiple ways to run Python, high-level data […]

3D Visualization

Date: 16 February 2024 3D visualization has been used in traditional scientific computing for several decades to visualize the results of multidimensional numerical simulations. In humanities, 3D visualizations have been […]

3D Visualization With XR Technology

Toronto Metropolitan University 350 Victoria Street, Toronto, Ontario, Canada

Have you ever wished you could stand in and study an imaginary or long-vanished space–from a work of literature or from a distant period in history, or perhaps a virtual […]