What do you think?
Rate this book
Practical Data & AI for Engineers: Applied Machine Learning, Data Pipelines, and AI Integration in Engineering Projects
Practical Data & AI for EngineersApplied Machine Learning, Data Pipelines, and AI Integration in Engineering Projects
In today’s engineering world, data and artificial intelligence are no longer optional — they are essential. Practical Data & AI for Engineers bridges the gap between traditional engineering practice and the new era of intelligent automation, predictive analytics, and digital twins.
This hands-on guide provides a real-world, engineering-focused introduction to applied machine learning, data management, and AI-driven solutions. It shows how engineers across disciplines — electrical, mechanical, civil, and industrial — can use data pipelines, models, and automation tools to enhance design, operations, and maintenance.
What You’ll LearnHow to collect, clean, and manage engineering data from sensors, PLCs, and SCADA systems.
Building data pipelines for real-time monitoring and analytics.
Practical machine learning models for predictive maintenance, fault detection, and optimization.
AI integration strategies for control systems, HVAC, power distribution, and manufacturing.
Tools and workflows for implementing AI at scale — from the field to the cloud.
With clear diagrams, simplified explanations, and step-by-step use cases, this book helps engineers adopt AI confidently without requiring advanced programming skills.
Whether you’re a design engineer, facility manager, or project leader, this book will guide you through every stage of your digital transformation — from understanding data sources to deploying your first AI model.
Part of the Practical Engineering Series by the Practicing Engineers Network (PEN)
Your trusted reference for engineering design, calculations, and modern technology applications.
In today’s engineering world, data and artificial intelligence are no longer optional — they are essential. Practical Data & AI for Engineers bridges the gap between traditional engineering practice and the new era of intelligent automation, predictive analytics, and digital twins.
This hands-on guide provides a real-world, engineering-focused introduction to applied machine learning, data management, and AI-driven solutions. It shows how engineers across disciplines — electrical, mechanical, civil, and industrial — can use data pipelines, models, and automation tools to enhance design, operations, and maintenance.
What You’ll LearnHow to collect, clean, and manage engineering data from sensors, PLCs, and SCADA systems.
Building data pipelines for real-time monitoring and analytics.
Practical machine learning models for predictive maintenance, fault detection, and optimization.
AI integration strategies for control systems, HVAC, power distribution, and manufacturing.
Tools and workflows for implementing AI at scale — from the field to the cloud.
With clear diagrams, simplified explanations, and step-by-step use cases, this book helps engineers adopt AI confidently without requiring advanced programming skills.
Whether you’re a design engineer, facility manager, or project leader, this book will guide you through every stage of your digital transformation — from understanding data sources to deploying your first AI model.
Part of the Practical Engineering Series by the Practicing Engineers Network (PEN)
Your trusted reference for engineering design, calculations, and modern technology applications.
Audible Audio
Published October 10, 2025
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
No one has reviewed this book yet.