What you'll learn

Deploying large language models in production often means high costs, latency, privacy concerns, and heavy infrastructure demands that many real-world use cases simply can’t accommodate. In this course, Foundations of Small Language Model Engineering, you’ll gain the ability to select, evaluate, and deploy small language models that meet your quality and performance requirements. First, you’ll explore what defines a small language model and how its architecture, hardware needs, and efficiency tradeoffs compare to those of LLMs. Next, you’ll discover how to compare leading model families, interpret model cards and licenses, and evaluate models against task-specific benchmarks rather than relying on generic leaderboards. Finally, you’ll learn how to set up a local serving environment, run inference, and establish a documented performance baseline. When you’re finished with this course, you’ll have the skills and knowledge of small language model engineering needed to confidently choose and deploy the right SLM for your production use case.