2023-2024 DASH Workshops | Sherman Centre for Digital Scholarship

Learn to analyze and visualize all kinds of data with the Data Analysis Support Hub’s 2023-2024 workshops. Register for the entire suite of DASH Workshops today. Watch all 2023-2024 recordings.

Data Visualization in R using ggplot2
September 14, 2023 | 1:30-2:30 p.m.
Facilitator: Subhanya Sivajothy, Data Analysis and Visualization Librarian
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This virtual workshop will provide an introduction to ggplot2, an open-source data visualization package for the statistical programming language R. This workshop will go over basic tips for creating visualizations and customizing the design of those graphs.

Introduction to R Programming
October 18, 2023 | 1:30-3:30 p.m.
Facilitator: Vivek Jadon, Data Specialist
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This beginner-level workshop will focus on basic concepts of R programming using R Studio. Various Data Types and Data Structures will be discussed, as well as basic data analysis in R. No prior knowledge of R programming is required. This workshop consists of a synchronous workshop session, which will be recorded and shared publicly afterward.

Introduction to Data Analysis with SPSS
November 15, 2023 | 1:30-3:30 p.m.
Facilitator: Vivek Jadon, Data Specialist
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This beginner-level workshop will introduce you to the basics of SPSS statistical software, how it works, and some basic descriptive statistics, statistical procedures and chart building features. No prior knowledge of SPSS is required. This session will be recorded and made available openly.

Introduction to Making and Sharing Maps with ArcGIS Pro – In Person
November 22, 2023 | 10:30-11:30 a.m.
Facilitator: Christine Homuth, Spatial Information Specialist
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ArcGIS Pro is a professional desktop Geographic Information Systems (GIS) program. It is a powerful data visualization tool that maps and analyzes data, depicting patterns and trends. This workshop is geared towards beginners new to ArcGIS or ArcMap users making the switch to ArcGIS Pro. Attendees will become familiar with ArcGIS tools that are available on campus, learn the ArcGIS Pro interface, symbolize data, and share the resulting map.

Machine Learning with Python: Image Classification
December 4, 2023 | 4:30-6:10pm
Facilitator: Amirreza Mousavi
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Learn image classification at this workshop, where we delve into image recognition using the PyTorch framework. Whether you’re a novice or have some prior experience in machine learning, this workshop is tailored to help you grasp the essentials of building image classification models.

Map Making for Absolute Beginners using QGIS – In Person
January 16, 2024 | 1:30-3 p.m.
Facilitator: Saman Goudarzi, Cartographic Resources Librarian
Recording Coming Soon
Designed for those who are curious about making maps but haven’t yet had the opportunity to learn. This workshop will provide a friendly introduction to geographic data and the mapping of this data using the geographic information system (GIS) software, QGIS. Absolutely no geography or quantitative background is necessary for an engaging experience.

Machine Learning with R: K-Means Clustering
January 26, 2024 | 4:30-6:10 p.m.
Facilitator: Amirreza Mousavi
Recording Coming Soon
This workshop will cover K-Means Clustering, a powerful machine-learning technique used for data segmentation and pattern recognition. K-Means is the most common clustering technique for unsupervised machine learning.

Hypothesis Test, Univariate, and Bivariate Analysis with R
February 13, 2024 | 1:30-3:30 p.m.
Facilitator: Humayun Kabir
Recording Coming Soon
In this beginner-level session, participants will learn the fundamentals of conducting hypothesis tests and performing univariate analysis using the R statistical software. This session will cover essential aspects of hypothesis testing, data preparation, and exploratory univariate analysis. Prior expertise in hypothesis testing or R may not be required.

Introduction to Python
February 14, 2024 | 1:30-3:30 p.m.
Facilitator: Vivek Jadon, Data Specialist
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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.

Machine Learning with R: Linear Regression
February 20, 2024 | 4:30-6:10p.m.
Facilitator: Humayun Kabir
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In this beginner-level session, attendees will learn the fundamentals of using R programming for machine learning, with a specific focus on linear regression. Prior expertise in R or machine learning may not be required.

Multivariable Analysis with R
February 27, 2024 | 4:30-6:10p.m.
Facilitator: Humayun Kabir
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In this beginner-level session, participants will learn the fundamentals of conducting multivariable analysis using the R statistical software. This session will cover essential aspects of multivariable analysis, including data preparation, regression techniques, and interpretation of results. Prior multivariable analysis or R expertise may not be required.

Machine Learning with R: Random Forest Classification Approach
March 8, 2024 | 4:30-6:10p.m.
Facilitator: Amirreza Mousavi
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Join us for a workshop on Random Forest. Random Forest is an ensemble machine learning technique used for both classification and regression tasks. It is based on the concept of decision trees, where multiple decision trees are trained on different subsets of the data, and their predictions are combined to produce a more accurate and robust final prediction.

Introduction to Document Typesetting and Scientific Publishing with LaTeX
March 13, 2024 | 1:30-3 p.m.
Facilitator: John Fink, Digital Scholarship Librarian
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LaTeX is a typesetting programming language used to produce beautiful documents. It especially excels at scientific, mathematic, and engineering specific layouts, but can be used to produce nearly any sort of document. This workshop will teach you the basics of LaTeX, including how to render things like chemical formulas with ease.

Web Scraping with Python’s Beautiful Soup
March 14, 2024 | 1:30-3 p.m.
Facilitator: Chelsea Miya, Sherman Centre Post-Doctoral Fellow
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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?

Machine Learning with R: Logistic Regression
March 22, 2024 | 4:30-6:10 p.m.
Facilitator: Humayun Kabir
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In this beginner-level session, attendees will learn the fundamentals of using R programming for machine learning, with a specific focus on logistic regression. No prior expertise in R or machine learning may be required.

Intermediate Python Programming
March 28, 2024 | 4:30-6:10 p.m.
Facilitator: Amirreza Mousavi
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Python, a versatile and user-friendly programming language, has found widespread use among scientists for a variety of applications. This workshop will include a brief review of variable types before moving on to functions, Modules, Classes, and some of Python’s important science libraries.

Survival Analysis with R
April 30, 2024 | 4:30-6:10 p.m.
Facilitator: Humayun Kabir
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In this beginner-level session, learners will explore the fundamentals of survival analysis using the R statistical software. The session will cover the basics of survival analysis, including data preparation, Kaplan-Meier survival curves, Cox proportional hazard models, and parametric hazard models. Survival analysis or R expertise may not be required.