AI Engineering: Designing Real-World Foundation Model Applications: 4 (Educera AI Reliability Series) - Softcover

Publishing, Educera

Softcover

ISBN 13: 9798268414677

Publisher: Independently published, 2025

Synopsis

AI Engineering: Designing Real-World Foundation Model Applications

🚀 Everyone’s talking about AI — but few know how to actually build something that works in production.
You don’t need another hype book. You need a roadmap to engineer, scale, and deploy real-world AI systems that perform.

⚙️ What This Book Delivers

This is not theory. It’s the how-to manual for professionals who want to turn large language models, multimodal systems, and generative AI tools into tangible business solutions.

You’ll learn how to:

• Architect foundation model pipelines from prototype to production

• Fine-tune, compress, and optimize models for performance and cost

• Integrate AI safely with APIs, cloud platforms, and real-time data streams

• Design evaluation frameworks that measure impact, not just accuracy

• Build governance and guardrails for privacy, fairness, and reliability

• Create scalable workflows for continuous deployment and iteration

💼 Who It’s For

• Machine learning engineers upgrading to applied AI engineering

• Software architects implementing LLMs and multimodal systems

• CTOs, founders, and product leaders driving AI-powered products

• Data scientists ready to move beyond notebooks into production

Tired of endless prototypes that never leave the lab?
This book bridges the gap between research and reality — giving you the frameworks, toolchains, and engineering mindset to build systems that ship, scale, and stay robust.

🔥 Ready to go from prompt tinkerer to AI engineer?
Grab your copy now — and start designing foundation model applications that actually deliver value.

Edition details

• Publisher: Independently published
• Publication date: 2025
• Language: English
• ISBN 13: 9798268414677
• Binding: Paperback
• Number of pages: 543