Programming Languages

In this workshop, we will convey the basics of deep learning in Python using keras on image datasets. You will gain a conceptual grasp of deep learning, work with example code that they can modify, and learn about resources for further study.

In a fast evolving artificial intelligence landscape, LLMs such as GPT have become a common buzzword. In the research community, their advantages and pitfalls are hotly debated. In this workshop, we will explore different chatbots powered by LLMs, beyond just ChatGPT. Our main goal will be to understand how LLMs can be used by researchers to conduct early-stage (or exploratory) research. Throughout the workshop, we will discuss best practices for prompt engineering and heuristics to evaluate the suitability of an LLM's output for our research purposes. Though the workshop primarily focuses on early-stage research, we will briefly discuss the use cases of LLMs in later stages of research, such as data analysis and writing.

This three-part interactive workshop series teaches you intermediate programming Python for people with previous programming experience equivalent to our Python Fundamentals: Parts 1-3 workshop. 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.

In this 2-part workshop series, we will provide an introduction to spatial analyses in R. We discuss the benefits of the additional ‘location' component that defines spatial data and how spatial data frames organize this information. Using the sf (simple features) and terra packages, we'll navigate fundamental operations for reading, writing, manipulating, and visualizing spatial data.