| Day | Perth | Adelaide | AEST | Duration | Content |
|---|---|---|---|---|---|
| Tue | 11:00am | 12:30pm | 01:00pm | ~30 mins | Landscape of Large Language Models |
| 11:30am | 01:00pm | 01:30pm | ~30 mins | Exercise 1 | |
| 12:00pm | 01:30pm | 02:00pm | ~25 mins | Capabilities of Large Language Models | |
| 12:25pm | 01:55pm | 02:25pm | ~30 mins | Exercise 2 | |
| 12:55pm | 02:25pm | 02:55pm | ~15 mins | Break | |
| 01:10pm | 02:40pm | 03:10pm | ~25 mins | Parameters of Large Language Models | |
| 01:35pm | 03:05pm | 03:35pm | ~30 mins | Exercise 3 | |
| 02:05pm | 03:35pm | 04:05pm | ~25 mins | Prompt Engineering | |
| 02:30pm | 04:00pm | 04:30pm | ~30 mins | Exercise 4 | |
| Wed | 11:00am | 12:30pm | 01:00pm | ~10 mins | Q&A |
| 11:10am | 12:40pm | 01:10pm | ~20 mins | Processing unstructured data to structured data | |
| 11:30am | 01:00pm | 01:30pm | ~30 mins | Exercise 5 | |
| 12:00pm | 01:30pm | 02:00pm | ~30 mins | Text analysis tasks | |
| 12:30pm | 02:00pm | 02:30pm | ~30 mins | Exercise 6 | |
| 01:00pm | 02:30pm | 03:00pm | ~15 mins | Break | |
| 01:15pm | 02:45pm | 03:15pm | ~45 mins | Architecture of Large Language Models | |
| 02:00pm | 03:30pm | 04:00pm | ~50 mins | Exercise 7 | |
| 02:50pm | 04:20pm | 04:50pm | ~10 mins | Next steps |
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👋 Welcome
Unstructured text data are often hard to process downstream by traditional statistical methods without processing it to a structured or standardised form. In this workshop, we discuss methods to process text data such as cleaning text entries, sentiment analysis, topic identification, topic modelling, and text summarisation. This workshop also serves as an introduction to large language models (LLMs) with demonstration of LLM-assisted text analysis. The workshop will help participants understand how LLMs can be integrated into existing workflows with hands-on experience. Practical applications will be demonstrated through R using OpenAI LLMs or local Ollama models. Participants will have access to all the slides and code used in the demonstration, so you can replicate the analyses and continue exploring LLMs on your own machines.
🕜 Schedule
The schedule is a rough guideline and may change slightly during the livestream.
- AEST includes Sydney, Melbourne, Canberra and Brisbane
📚 Slides
️ Exercises
License
These workshop materials by Emi Tanaka is licensed under CC BY-NC-ND 4.0 – which means you can share the link with your colleagues, peers, friends, family and so on, so long as due credit is given to the author. However, you cannot commercialise or create derivatives from this work without the permission of the author (emi.tanaka@anu.edu.au).