Beginning Llamafile
This course is part of Generative AI Fundamentals.
This practical course teaches you how to harness the power of large language models through API endpoints using the llama.cpp server. You'll learn to configure model behavior, handle requests efficiently, and integrate language model capabilities into applications. The course covers installation of Cosmopolitan Libc toolkit, local model deployment with llamafile, and API interaction for NLP tasks. With hands-on exercises and code examples, you'll master serving language models in production environments.
Instructors:
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What you'll learn
Install and configure the Cosmopolitan Libc toolkit
Deploy language models locally using llamafile
Create portable command-line interfaces
Implement REST API endpoints for NLP tasks
Configure and optimize model serving behavior
Skills you'll gain
This course includes:
PreRecorded video
Quizzes, Ungraded Labs, Discussion Prompts
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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There is 1 module in this course
The course focuses on practical implementation of language model deployment using llamafile. Students learn to work with the Cosmopolitan Libc toolkit for creating portable applications, understand llamafile packaging and licensing, and develop REST API endpoints for language model serving. The curriculum covers system metrics monitoring, server configuration, and hands-on experience with tools like curl and Python for API interaction.
Getting Started with Mozilla Llamafile
Module 1
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Generative AI Fundamentals
Instructors
Executive in Residence and Founder of Pragmatic AI Labs at Duke University
Noah Gift is the founder of Pragmatic AI Labs and serves as an Executive in Residence at Duke University, where he lectures in the Master of Interdisciplinary Data Science (MIDS) program. He specializes in designing and teaching graduate-level courses on machine learning, MLOps, artificial intelligence, and data science, while also consulting on machine learning and cloud architecture for students and faculty. A recognized expert in the field, Gift is a Python Software Foundation Fellow and an AWS Machine Learning Hero, holding multiple AWS certifications, including AWS Certified Solutions Architect and AWS Certified Machine Learning Specialist. He has authored several influential books, such as Practical MLOps, Python for DevOps, and Pragmatic AI, and has published over 100 technical articles across various platforms, including Forbes and O'Reilly. His extensive industry experience includes roles as CTO and Chief Data Scientist for notable companies like Disney Feature Animation, Sony Imageworks, and AT&T, contributing to major films like Avatar and Spider-Man 3. Gift's work has generated millions in revenue through product development on a global scale. He actively consults startups on machine learning and cloud architecture while leading initiatives to enhance data science education.
Adjunct Assistant Professor at Duke University
Dr. Alfredo Deza is an Adjunct Assistant Professor in the Pratt School of Engineering at Duke University, where he teaches courses on machine learning, programming, and data engineering. He has been involved in academia for several years, focusing on innovative teaching methods and practical applications of technology. Dr. Deza co-authored the book Practical MLOps and has published several other works related to Python and machine learning. His teaching includes courses such as Python Bootcamp and advanced data engineering topics, and he actively develops online courses available on platforms like Coursera. In addition to his academic role, Dr. Deza works in developer relations at Microsoft, leveraging his extensive experience in software engineering and cloud computing to enhance educational content and support for students and faculty. He collaborates with various universities worldwide, including Georgia Tech and Carnegie Mellon University, to promote knowledge sharing in the field of technology and data science.
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