Foundations of Local Large Language models

Duke introduces local model operations before studying production workflows, performance and responsible AI. Its published description names tools such as Hugging Face Candle and Mozilla llamafile. The course is useful for comparing running a model on your own machine with calling a hosted model service.

What you will learn

• Set up a local language-model environment.
• Compare interfaces and APIs for local model use.
• Identify performance and responsibility concerns in local LLM operations.

Who this suits

Beginners with introductory programming experience, a basic cloud-computing background and familiarity with a development text editor.

Before you enroll

Check the hardware and model-file requirements before downloading. Local execution changes where data is processed but still requires attention to model licenses, software updates and output quality.

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Put it into practice

Run a small permitted local model and record its memory use and response time. Compare two prompts and document whether the output meets a defined task requirement.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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