Technical Component Intoduction

This unit of the journey provides context around the technologies we encounter & a few analogies to facilitate understanding the purpose of guided lab in the next section. Feel free to skip ahead if you just want to get started.

Why this technical course?

A Formula One Driver doesn’t need to know how to build an engine to be an F1 champion. However, she/he needs to have a mechanical sympathy, which is understanding of the car’s mechanics to drive it effectively and get the best out of it.

The same applies to AI. We don’t need to be AI experts to harness the power of large language models, but we do need to develop a certain level of "technological awareness" about how LLM Models are trained, selected, operationalized, delivered, inferred from, fined-tuned, augmented and kept up-to-date. Not just as users, but as aficionados who understand the underlying components to effectively communicate with clients, partners, and co-workers.

The true power lies in the platform that enables us to harness a diverse range of AI models, tools, infrastructure and operationalize our ML projects.

That platform, OpenShift AI, is what we learn to create, configure, and utilize to Serve LLM Models in this quick course.