GPU Server and LLM Implementation
Learn to set up GPU servers, implement local language models, and build AI applications. Master open-source model deployment and agent integration.
Learn to set up GPU servers, implement local language models, and build AI applications. Master open-source model deployment and agent integration.
This comprehensive course explores GPU server implementation and Local Language Models (LLMs). Students learn to navigate the GPU market, set up virtual machines with GPU capabilities, and implement local LLM servers. The curriculum covers practical aspects of downloading and deploying open-source models, building Python applications powered by LLMs, and designing with AI agents. Whether you're a developer, data scientist, or AI enthusiast, you'll gain hands-on experience in creating and managing local AI infrastructure for intelligent applications.
Instructors:
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What you'll learn
Understand GPU market dynamics and infrastructure requirements
Set up and configure GPU-enabled virtual machines
Implement local LLM servers using open-source models
Develop Python applications powered by local LLMs
Master LLM Studio setup and configuration
Create and deploy AI agents for practical applications
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 4 modules in this course
This course provides a comprehensive introduction to GPU server implementation and Local Language Models. Students learn about the current GPU market landscape, infrastructure setup, and practical applications of LLMs. The curriculum covers essential topics including virtual machine configuration, open-source model deployment, local server implementation, and AI agent integration. Through hands-on exercises, participants develop the skills needed to build and manage their own AI infrastructure for various applications.
Intro and set up
Module 1
Large Language Model server setup
Module 2
Building a local chat application
Module 3
Using AutoGen
Module 4
Fee Structure
Instructor
Veteran Educator and Data Science Expert at Duke University
Derek Wales is an accomplished Adjunct Professor at Duke University, where he leverages his extensive background in engineering and data science to educate the next generation of professionals. A graduate of West Point with a degree in Electrical Engineering, Derek served ten years as an Engineer Officer in the Army, where he designed innovative technologies such as a laser target location module. After his military career, he earned degrees from Duke's Master of Interdisciplinary Data Science (MIDS) and Weekend Executive MBA (WEMBA) programs. Transitioning into the tech industry, he has worked as a data scientist and product manager, applying his skills in various domains. At Duke, he teaches courses on topics ranging from virtualization to generative AI, actively engaging students with practical insights from his diverse experiences. Derek's commitment to education and innovation positions him as a key figure in bridging military discipline with advanced data science applications.
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