The Self-Taught AI Engineering Manual : One Clear Roadmap to Build Real Scalable & Human-Centered AI Systems Agentic LLM Apps & Secure System Design to Become an Independent Builder
Language: English
Published by Publishdrive Inc. Sep 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 36.94
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Add to basketItem description from seller
Neuware - AI Engineer Reveals the Practical, Clear Roadmap to Build Real, Production-Ready AI Systems Without Waiting to Feel Ready! Have you finished another course and still frozen in front of an empty file Do you keep postponing AI Engineering because you doubt your Python or your math is good enough If today's AI models, LLMs, and frameworks became obsolete tomorrow, experienced AI engineers wouldn't be lost. Why Because they master the evergreen fundamentals and core skills needed to build AI systems independently. This book gives you those evergreen fundamentals & skills to turn ideas into real AI systems, create LLM apps and AI agents, and take working demos into the real world without constantly wondering what to learn next. Here's a quick preview of what's inside: One Clear Roadmap: Learn what matters, what you actually need to know, and what you can ignore with a step-by-step plan that cuts through the chaos.- Build Without Tutorials: Design complete AI systems from an empty file instead of copying step-by-step guides.- Skills That Actually Matter: Get practical skills you can use in real projects without chasing every new tool, trend, or technology.- Only the Fundamentals You Need: Focus on the Python, programming, and math that actually matter for AI Engineering without unnecessary complications.- Stay in Control: Evaluate, test, verify, and improve AI outputs instead of blindly trusting what the model gives you.- From Prototype to Real Systems: Take AI projects beyond demos and turn them into real, working systems.- Make Better Technical Decisions: Develop the necessary judgment to choose, evaluate, and improve AI solutions with confidence. You'll stop feeling like a beginner and become capable of turning your own ideas into real AI systems. You'll know what matters, what to do next, and how to make technical decisions with confidence. Get your copy today and start mastering AI Engineering before it's too late.…
Seller Inventory # 9798898434298
- Title
- The Self-Taught AI Engineering Manual : One Clear Roadmap to Build Real Scalable & Human-Centered AI Systems Agentic LLM Apps & Secure System Design to Become an Independent Builder
- Author
- Isaac Vance
- Publisher
- Publishdrive Inc. Sep 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798898434298
- Item weight
- 626 grams
- Dimensions
- 279x216x14 mm
AI Engineer Reveals the Practical, Clear Roadmap to Build Real, Production-Ready AI Systems Without Waiting to Feel Ready!
Have you finished another course and still frozen in front of an empty file?
Do you keep postponing AI Engineering because you doubt your Python or your math is good enough?
If today’s AI models, LLMs, and frameworks became obsolete tomorrow, experienced AI engineers wouldn’t be lost. Why? Because they master the evergreen fundamentals and core skills needed to build AI systems independently.
This book gives you those evergreen fundamentals & skills to turn ideas into real AI systems, create LLM apps and AI agents, and take working demos into the real world without constantly wondering what to learn next.
Here’s a quick preview of what’s inside:
One Clear Roadmap: Learn what matters, what you actually need to know, and what you can ignore with a step-by-step plan that cuts through the chaos.
• Build Without Tutorials: Design complete AI systems from an empty file instead of copying step-by-step guides.
• Skills That Actually Matter: Get practical skills you can use in real projects without chasing every new tool, trend, or technology.
• Only the Fundamentals You Need: Focus on the Python, programming, and math that actually matter for AI Engineering without unnecessary complications.
• Stay in Control: Evaluate, test, verify, and improve AI outputs instead of blindly trusting what the model gives you.
• From Prototype to Real Systems: Take AI projects beyond demos and turn them into real, working systems.
• Make Better Technical Decisions: Develop the necessary judgment to choose, evaluate, and improve AI solutions with confidence.
You’ll stop feeling like a beginner and become capable of turning your own ideas into real AI systems. You’ll know what matters, what to do next, and how to make technical decisions with confidence.
Get your copy today and start mastering AI Engineering before it’s too late!
"Synopsis" may belong to another edition of this title.
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