Does this program cover the cost of API access?

In Course 1 and 2, you will have access to optional activities where you will be guided to access Llama models via API. The cost of API credits is not included in this program and will be at your own cost. Some API providers may provide free credits when you first register with their platform. Please check with the providers directly to confirm.

What will I get if I subscribe to this Certificate?

When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

What is the refund policy?

If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

Inference techniques for local and cloud LLM deployment

Inference techniques for local and cloud LLM deployment

This course is part of Building Generative AI Apps with Llama Professional Certificate

Instructor: Taught by Meta Staff

Included with Coursera Plus

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Advanced level

Recommended experience

1 hour to complete

Flexible schedule

Learn at your own pace

Advanced level

Recommended experience

1 hour to complete

Flexible schedule

Learn at your own pace

What you'll learn

The principles of LLM inference and prompt pipelines for real-world tasks.
Running small and medium LLMs locally with Ollama and deploying larger models in the cloud using Python.
Building and documenting LLM-powered tools ready for real-world use.

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English

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This course is part of the Building Generative AI Apps with Llama Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

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Frequently asked questions

Developers, entrepreneurs, and technical professionals with 1-2 years of Python knowledge who want to build AI-enabled assistants. Ideal for those looking to upskill in generative AI development or create practical business solutions using Llama models.

1-2 years of Python programming experience (for those who need to meet this prerequisite, start with the Meta Programming in Python course)

Familiarity with command-line interfaces

Understanding of basic software development concepts

Basic knowledge of REST APIs

In this program, you will be guided to access the Llama 4 Scout 17B and Llama 3.1 8B models via API in Courses 1 and 2. The course content includes examples using one of the API providers, but you are free to choose any provider that offers access to Llama models for your learning experience. Examples of such providers include Together AI, Groq, Hugging Face, and others.

In Course 3, you will be guided to use the Llama 3.1 8B model in a local environment. Llama models are available from multiple sources, with the best place to start being https://www.llama.com.

Models are also hosted and distributed by partners such as Amazon Web Services, Microsoft Azure, Google Cloud, IBM Watsonx, Oracle Cloud, Snowflake, Databricks, Dell, Hugging Face, Groq, Cerebras, SambaNova, and many others. See the Llama.com FAQ for more information.

In Courses 1 and 2, you will access Llama models through an API. No additional device requirements are needed, but you will need internet access and to select your own API provider.

In Course 3, you will learn to use Llama in a local environment. Hardware requirements vary based on the specific Llama model being used, latency, throughput and cost constraints. For the larger Llama models to achieve low latency, one would split the model across multiple inference chips (typically a GPU) with tensor parallelism. Llama models are known to execute in a performant manner on a wide variety of hardware including GPUs, CPUs (both x86 and ARM based), TPUs, NPUs and AI Accelerators. The smaller Llama models typically run on system-on-chip (SOC) platforms found on PC, Mobile and other Edge devices.

See the Llama.com FAQ for more information.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.