Introducing LLMs as a Learning Tool
Last updated on 2026-07-30 | Edit this page
Overview
Questions
- What do I want to learn?
- What AI chatbots are available to me?
- How do I get started?
Objectives
- Understand learning through challenge
- Identify a learning goal
- Choose an AI chatbot
- Use R to explore data
Generative AI As A Learning Tool
Generative models and agents, including LLMs, can be used to automate a wide variety of tasks, at work and in our lives. But automating a task while we are still learning how to do it can limit our learning and our ability to build up more complex and creative skill sets.
We can use AI tools to positively support our learning journey instead. In this class we will explore and practice some ways that we can use Large Language Models to inform, challenge and support us as we learn how to write software code to analyse research data.
Choosing An AI Partner
There are many popular AI models available online, including:
In addition, institutions might run their own, local copies of models like such as DeepSeek or Mistral:
Choosing A Programming Language
Researchers use many different programming languages to solve problems in data analysis and modeling. This course provides examples in Python and R. Both of these languages are widely used in research computing, since they are open source, freely available and have large user communities who contribute useful code.
You could use the approach in this course to learn other languages too, but remember that the more widely used a language is, the better it is represented in AI training data, and the better an LLM will support it.
Challenge : What Tools Do We Have
Do you know what Generative AI tools are available and supported in your environment?
Discuss with each other and with your instructor:
- What AI tools have you heard of?
- Which are most often used in your institution/s?
- Are there any special policies that affect your choice?
- Can you access your tool of choice right now?
Choose an appropriate LLM to use today and open a session.
Getting Started with R
R Basics
- Run
3 + 5in R Console - Create variable with data e.g.
weight_kg <- 55 - View contents e.g.
weight_kg
Load Data
- Introduce gapminder: country, year, pop, continent, lifeExp, gdpPercap
- Download https://swcarpentry.github.io/r-novice-gapminder/data/gapminder_data.csv
R
gapminder <- read.csv( "gapminder_data.csv" )
head( gapminder )
summary( gapminder )
- Generative AI tools like LLMs can either hinder or help our learning
- We can use them to support our learning through explanations, prompting and challenges
- Choice of specific tools might depend on local policies.