llm-engineering-101

Getting started with prompting and engineering with LLMs.

Example workshop

• Introduction to the workshop or course
• Mentimeter and other prep
• Introduction to AI (symbolic vs discriminative vs generative) and LLMs (how are they trained?)
• Chat applications and hallucinations (hands on)
• Get everyone up and running with the API, see Notebook 1
• Using the API, trying some things, and a bit about tokens, see Notebook 2
• More stuff: tools or functions, agents, embeddings, and RAG; see Notebook 3

If this is for an idea jam or hackathon, then you can continue:

• Brainstorming applications (about 45-60 minutes)
• Forming projects and teams (about 45-60 minutes)

See also

We maintain various other repos related to machine learning and artificial intelligence:

• promptly for more on prompting and pitfalls in generative AI.
• ml-pitfalls for more on pitfalls in discriminative machine learning, another series of events.
• ai-upskill-events for a repo describing Equinor's company upskill events and materials.