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.

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.

Date: 14 February 2024 We’ll be presenting the main features of Stylo, a web-accessible semantic text editor for writing in the humanities and social sciences. Since the project’s launch in 2017, one of its objectives has been to provide a tool capable of changing and improving the academic publishing chain, particularly the workflow of journals […]

Date: 14 February 2024 This workshop will introduce the Text Encoding Initiative (TEI): the de facto standard in the humanities for creating digital texts. In this workshop, we will discuss the scholarly and technical affordances are of using the TEI, answering why it is that so many digital humanities resources—including Early English Books Online (EEBO), […]

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?

Date: 15 February 2024 Using a single environment for all stages of your research project can help you organize your work. To this end, our team recommends JupyterLab, a software that logs code, text, equations, graphs and visualizations in a single document. This tool can also execute the lines of a program one at a […]

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 some academic fields such as statistics, biology, bioinformatics, data mining, data analysis, and linguistics. This introductory course does not assume any prior knowledge: it will […]

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 collections such as lists and dictionaries, using Python for data processing and manipulation, and data visualization. This short lecture-style course will be followed by a […]

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 mostly restricted to specialized areas such as game engines, architectural renderings, virtual environments, photogrammetric processing, and visualization of point cloud data. In this short course, […]

How does deep learning really work? What exactly are those large language models everybody talks about? How can I build a neural network? What is NLP? This presentation will answer these questions in a non-technical manner to give you a high-level understanding of a discipline that has become crucial in all fields of research. The […]

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 creation of a famous thought experiment or a speculative model of something that doesn’t exist in the real world? 3D visualization can grant that wish. […]