AI Engineering Use Cases and Projects on AWS: Production-Grade LLM Systems
46mIntermediate2025-03-12
Authors
Noah Gift
MLOps Expert | Solopreneur | Author | Adjunct Professor | CTO
Pragmatic AI Labs
Course details
Discover the intricate architecture of production-level large language models (LLMs) using Rust on AWS. Instructor Noah Gift covers an array of key topics, including the Ollama DeepSeek-R1, Claude, and other cutting-edge LLM systems, as well as open-source strategies and multimodel workflows. Along the way, get hands-on experience with YAML prompts and proxy routing to optimize your language models. Designed for AI engineers, developers, and tech enthusiasts, this course provides the skills necessary to advance your expertise in AI and machine learning. By the end of this course, you’ll be prepared to deploy and scale sophisticated language models in a production-grade environment, staying ahead of the curve in the rapidly evolving field of AI.
Skills covered
Programming FoundationsArtificial Intelligence FoundationsCloud ServicesCloud PlatformsArtificial Intelligence (AI)Cloud ComputingSoftware DevelopmentOne-Off
Concepts
0. Introduction
- 01 - Getting started
1. Production LLM System Architecture
- 02 - Rust LLM project extension
- 03 - Ollama DeepSeek-R1 and Claude
- 04 - Open-source strategy walkthrough
- 05 - YAML prompts with Rust walkthrough
- 06 - Multimodel workflow walkthrough
- 07 - Rust-model proxy routing walkthrough
- 08 - Rust Cargo Lambda serverless capstone challenge
- 09 - AI-engineering capstone