Data

AI for Coding: Fundamentals of LLMs

April 9, 2026, 1:00 pm to 1:45 pm

Date: Thursday, April 9, 2026
Time: 1:00pm - 1:45pm
Presenter: Grigory Artazyan, Jeremy Buhler
Location: Online

The first in a three-part series on AI for Coding, this workshop introduces fundamental concepts that will help you engage efficiently with AI in coding tasks. Participants will use the "prompt formula" to write better prompts and learn why specificity matters. 

What you will learn:

  • How LLMs work and why tokens matter
  • The prompt formula: context + task + constraints + format
  • How to write focused, specific prompts that work
  • Why conversation history affects your results


About the series: AI for Coding: Data Analysis with Cursor consists of three 30-minute workshops designed to help you use Large Language Models (LLMs) to support exploratory data analysis. We will introduce fundamental concepts, practice breaking down problems into actionable components, and use the Cursor IDE to integrate AI and code more efficiently. Each workshop focuses on a single topic with 30 minutes of teaching, followed by an optional 15 minutes for questions, discussion, and practice.

To build on other UBC Library Research Commons workshops the coding examples are in R, but the principles apply to any programming language. Beginners are welcome; participants who have some experience with R and the tidyverse packages will find it easier to follow along.

Register for other workshops in the series:

  1.  Fundamentals of LLMs - April 9, 2026, 1-1:45pm
  2.  Data Analysis & Visualization - April 16, 2026, 1-1:45pm
  3.  Building with Cursor - April 23, 2026, 1-1:45pm
Campus/Source

https://libcal.library.ubc.ca/event/4009863


  • Data
  • Research Commons

First Nations land acknowledegement

We acknowledge that UBC's two main campuses are located on the traditional, ancestral and unceded territories of the xwmə0– kwəyˇəm (Musqueam) and Syilx (Okanagan) peoples, and that UBC’s activities take place on Indigenous lands throughout British Columbia and beyond.


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