ARTIFICIAL INTELLIGENCE · 3 WEEKS · 81 LESSONS
Applied Local Large Language Models
Learn to deploy and operate local large language models using modern tools and best practices. Gain hands-on experience with llamafile, Rust Candle, and production-ready LLM implementations.
Master the deployment and operation of local large language models (LLMs) through hands-on experience with tools like llamafile and Rust Candle. This comprehensive course covers fundamental concepts, practical implementation techniques, production workflows, and responsible AI practices, enabling you to effectively build, evaluate, and deploy local LLM solutions while understanding their benefits, risks, and ethical considerations.
01 — What learners say
Real feedback from real learners.
“The Rust Fundamentals course was fantastic for formalizing my base Rust knowledge. It was well-paced for both beginner and experienced developers.”
“The course was incredibly informative and well-structured. I gained practical skills that immediately applied in my work, making it a highly valuable learning experience.”
“The course on AI Fundamentals is not only engaging but also practical. Having worked with AWS before, the way it explained Azure cncepts made switching seamless and easy to grasp.”
“I can say that it's a great series of courses for those who are looking to practical MLOps knowledge.”
“This course got clear videos, exercises, and questions, and there are extra resources too. When you're done, you'll have a solid foundation to dive into topics like DevOps or ML.”
02 — Why this course
What you'll walk away with.
Master the deployment and operation of local large language models (LLMs) through hands-on experience with tools like llamafile and Rust Candle. This comprehensive course covers fundamental concepts, practical implementation techniques, production workflows, and responsible AI practices, enabling you to effectively build, evaluate, and deploy local LLM solutions while understanding their benefits, risks, and ethical considerations.
Understand core concepts of local LLMs including benefits, risks, and implementation approaches
Deploy and operate local LLMs using llamafile and Rust-based tools like Candle
Evaluate real-world performance and implement production workflows for local LLM applications
Master retrieval augmented generation (RAG) techniques for enhanced LLM capabilities
03 — Syllabus
3 weeks, 81 lessons total.
- Meet your course instructor NOAH gift
- Meet your course instructor Alfredo DEZA
- Connect with your instructors
- Course structure
- Key terms
- Introduction
- Key terms
- Coding ELO in python
- Coding ELO in RUST
- Coding ELO in r
- Coding ELO in julia
- Chatbot arena
- Key terms
- Profit sharing concepts
- Tragedy of the Genai commons
- Game theory of Genai
- Perfect competition
- Negative Externalities
04 — For teams
Custom training for your company.
We're ready to deliver this and other courses to your team. We accommodate different requirements and are flexible with seat count.
- +Bulk pricing available
- +Customizable content
- +Ready to start on your schedule
05 — Individual access
Simple, straightforward pricing.
Full platform access — every current and future course — priced so cost isn't what decides whether you learn.
No commitment required. Cancel anytime.