Local LLM Development and Deployment
Master the setup and deployment of Large Language Models locally, using tools like Hugging Face and Mozilla llamafile.
Master the setup and deployment of Large Language Models locally, using tools like Hugging Face and Mozilla llamafile.
This practical course teaches how to effectively deploy and interact with Large Language Models (LLMs) on local machines. Students learn to set up local environments, integrate various LLM tools, and develop applications using web interfaces and APIs. The curriculum covers essential frameworks like Hugging Face Candle and Mozilla llamafile, providing hands-on experience in local LLM deployment and interaction techniques.
Instructors:
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What you'll learn
Set up and configure local environments for LLM deployment
Master integration of various LLM tools and frameworks
Develop applications using web interfaces and APIs
Implement efficient local deployment strategies
Utilize Hugging Face Candle for LLM capabilities
Integrate Mozilla llamafile effectively
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This comprehensive course focuses on deploying and managing Large Language Models in local environments. Beginning with fundamental concepts, students learn to set up and configure various LLM tools and frameworks. The curriculum covers interaction through web interfaces and APIs, emphasizing practical implementation using frameworks like Hugging Face Candle and Mozilla llamafile. Special attention is given to efficiency and optimization in local LLM deployment.
Fee Structure
Instructors
30 Courses
Pioneering Tech Leader & AI Educator Shaping the Future of Machine Learning
Noah Gift is a distinguished technology leader and founder of Pragmatic AI Labs with a remarkable 30-year career spanning film, TV, telecom, social networks, startups, and big data, currently serving as an Executive-in-Residence at Duke University. As an AWS ML Hero and Python Software Foundation Fellow, he has authored best-selling books through O'Reilly and Pearson on DevOps, MLOps, data engineering, and cloud computing that are widely adopted by major universities. His expertise in MLOps, data engineering, cloud architecture, and Rust programming has led him to teach thousands of students across prestigious institutions including Duke, Northwestern, UC Berkeley, University of San Francisco, and UC Davis, while also collaborating with Caltech and JPL on automated IT systems. Gift's impact extends beyond academia through his work as a startup CTO, his role in developing scalable distributed systems, and his contributions as a keynote speaker at conferences focused on cloud development and ethical AI use, holding certifications from AWS, Google, and Microsoft, and having published over 100 technical works while conducting workshops for organizations like NASA, PayPal, and PyCon.
20 Courses
A Technology Educator and Former Olympic Athlete Pioneering AI Innovation
Alfredo Deza embodies a unique combination of athletic excellence and technological expertise, transitioning from a distinguished career as Peru's first World Junior Champion in high jump and 2004 Olympian to becoming a leading voice in technology education and development. Currently serving as a Principal Cloud Advocate at Microsoft and Adjunct Assistant Professor at Duke University's Pratt School of Engineering, Deza has built an impressive career spanning nearly two decades in software engineering and education. His academic contributions extend through guest lectures at prestigious institutions including Oxford University, Georgia Tech, and Carnegie Mellon University, where he shares expertise in machine learning, cloud computing, and programming languages. As an accomplished author, he has co-authored several influential books with O'Reilly Media, including "Practical MLOps" and "Python for DevOps," while developing comprehensive courses on Coursera covering topics from large language models to Rust programming. His teaching portfolio at Duke includes graduate-level courses in machine learning operations and Python programming, reflecting his commitment to making complex technical concepts accessible. Deza's expertise encompasses a broad spectrum of technologies, including Azure, MLOps, DevOps, Python, Rust, and Databricks, which he leverages to bridge the gap between academic theory and industry practice. His unique perspective, shaped by his background as an Olympic athlete, influences his approach to teaching and technology, emphasizing the importance of continuous learning and knowledge sharing in the rapidly evolving field of artificial intelligence and cloud computing.
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