Programming Languages

Python Data Wrangling and Manipulation with Pandas

October 19, 2021, 10:00am
Pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive. It enables doing practical, real world data analysis in Python. In this workshop, we'll work with example data and go through the various steps you might need to prepare data for analysis.

Python Text Analysis: Word Embeddings

October 25, 2023, 2:00pm
How can we use neural networks to create meaningful representations of words? The bag-of-words is limited in its ability to characterize text, because it does not utilize word context.

R Visualization

May 27, 2022, 9:00am
This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data. We will also explore the basic grammar of graphics, including the aesthetics and geometry layers, adding statistics, transforming scales, and coloring or panelling by groups. You will learn how to make histograms, boxplots, scatterplots, lineplots, and heatmaps as well as how to make compound figures.

Bash + Git: Introduction

May 2, 2024, 2:00pm
This workshop will start by introducing you to navigating your computer’s file system and basic Bash commands to remove the fear of working with the command line and to give you the confidence to use it to increase your productivity. And then working with Git, a powerful tool for keeping track of changes you make to the files in a project.

MaxQDA: Introduction

February 14, 2023, 10:00am
This two-hour introductory workshop will teach you MaxQDA from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the MaxQDA software, upload multiple forms of data then how to use manual and autocode features. We will review some of the additional analytic features including visual, memo and the Questions, Themes and Theories (QTT) tools. We will briefly touch on the MaxQDA Team cloud-based version. Instructors will share recommended resources.

Python Introduction to Artificial Neural Networks

November 17, 2021, 9:00am
This workshop presents a brief history of Artificial Neural Networks (ANNs) and an explanation of the intuition behind them; a step-by-step reconstruction of a very basic ANN, and then how to use the scikit-learn library to implement an ANN for solving a classification problem.

MaxQDA Fundamentals

January 10, 2024, 9:00am
This two-hour introductory workshop will teach you MaxQDA from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the MaxQDA software, upload multiple forms of data then how to use manual and autocode features. We will review some of the additional analytic features including visual, memo and the Questions, Themes and Theories (QTT) tools. We will briefly touch on the MaxQDA Team cloud-based version. Instructors will share recommended resources.

GIS & Mapping Community of Practice meetup

February 7, 2023, 11:00am
This month's "welcome back" meetup & pizza social is hosted by the D-Lab! We'll meet in the D-Lab Collaboratory and learn about the D-Lab's services, trainings, and spaces. Plus, of course, opportunities to chat with other folks on campus about what they're doing with GIS & mapping.

Python Fundamentals: Parts 1-4

February 1, 2022, 2:00pm
This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Python Machine Learning Fundamentals: Parts 1-2

October 4, 2022, 2:00pm
This workshop introduces students to scikit-learn, the popular machine learning library in Python, as well as the auto-ML library built on top of scikit-learn, TPOT. The focus will be on scikit-learn syntax and available tools to apply machine learning algorithms to datasets. No theory instruction will be provided.