AI Orchestration: Designing the Prototype Architecture and Data Strategy
1h 46mIntermediate2025-01-23
Authors
Noah Gift
MLOps Expert | Solopreneur | Author | Adjunct Professor | CTO
Pragmatic AI Labs
Course details
This course covers the fundamentals and practical applications of AI orchestration. It is structured to provide both theoretical knowledge and hands-on experience in integrating and managing AI models across different computing environments. Instructor Noah Gift explores architectures, strategies, and best practices for building robust AI solutions. Gain practical experience in balancing different deployment strategies, managing data flow, and optimizing system performance across various computing environments.
Skills covered
Business IntelligenceServer AdministrationArtificial Intelligence FoundationsArtificial Intelligence (AI)Network and System AdministrationData ScienceBusiness Analysis and StrategyOne-Off
Concepts
Introduction
- Course introduction
- Course overview
- AI orchestration overview
Prompt Engineering Fundamentals
- Prompt engineering pyramid
- Chain of thought prompt Rust
- Chain of thought Rust prompt demo
AI Systems and Architecture
- Explaining chain of thought Rust prompt
- Caching for AI
- Optimizing local RAG
- Local vs. cloud models
Tools and Implementation
- Llamafile getting started Gemma
- Llamafile simple
- Rust hello world project structure
- AWS spot deploy ML
- Hugging Face workflow models
- GitHub AI models workflow
- Ollama local demo
- Technical training approaches
- Ollama modelfile rust debugger
- Effective AI engineering learning
- AI orchestration local workstation
- Using TMUX on Linux
- Using NVIDIA-SMI
- Ollama architecture
- Using Zenith GPU monitoring
- Compiling Rust candle GPU
Conclusion
- Summary