Python for Engineers and Scientists

A Complete Hands-On Journey from Core Python to Numerical and Scientific Applications
1. Auflage 2026
ISBN: 979-8-8688-3164-5
Verlag: APRESS L.P.

Buch, Englisch, 605 Seiten, Format (B × H): 178 mm x 254 mm

This book equips technical professionals with a complete, structured path to mastering Python for real-world engineering and scientific applications. As Python becomes central to research labs, automation, simulation, and data-driven engineering, the learning curve remains steep. This book bridges that gap with a practical roadmap from fundamentals to professional-grade scientific computing.

The book begins by building a strong programming foundation—covering Python’s architecture, essential syntax, data structures, modules, functions, control flow, and object-oriented design. Readers learn not only to write Python, but the language behaves the way it does, ensuring deep understanding and strong problem-solving skills. From there, the focus shifts to practical engineering tools. Dedicated chapters train readers in file handling, math modules, and key scientific libraries including NumPy, SciPy, Pandas, and Matplotlib, enabling efficient computation, signal processing, data analysis, and high-quality visualization. Advanced chapters then showcase Python’s versatility through GUI development with Kivy, database work with SQLAlchemy, and hands-on control system modeling and analysis. Each topic is rooted in industry and academic scenarios, making the content directly applicable to automation, simulation, data workflows, and engineering computation.

Whether you're a student building foundational skills or a professional modernizing engineering workflows, this guide provides the programming depth, scientific tools, and applied knowledge needed to use Python confidently for prototyping, simulation, analysis, and automation. It is the one-stop resource for mastering Python in technical disciplines.

What you will learn:

Learn core Python programming concepts, including variables, loops, functions, and object-oriented principles in a scientific and engineering context.

Build strong skills in key scientific Python libraries such as NumPy, Pandas, Matplotlib, and SciPy for computation, analysis, and visualization.

Apply Python to real-world engineering scenarios, including dynamic control systems and automation workflows.

Develop interactive engineering applications by creating graphical user interfaces (GUIs) with Kivy.

Who this book is for:

This book is intended for practicing engineers and scientists across various disciplines of engineering who need to use Python for complex problem-solving, simulation, and data analysis in their work.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Freitas, Carlos Márcio da Silva

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen

Inhaltsverzeichnis

Chapter 1: Python Fundamentals for Engineers.-Chapter 2: Variables, Data Types, and Collections Basics.-Chapter 3: Working Deeply with Collections.-Chapter 4: Modules, Packages, and the Python Ecosystem.-Chapter 5: Functions and Reusable Code.-Chapter 6: Control Flow and Error Handling.-Chapter 7: Object-Oriented Programming for Engineers.-Chapter 8: Working with Files and Paths.- Chapter 9: Mathematical Foundations in Python.-Chapter 10: Data Visualization with Matplotlib.-Chapter 11: Numerical Computing with NumPy.-Chapter 12: Advanced Scientific Computing with SciPy.-Chapter 13: GUI Development with Kivy.- Chapter 14: Data Analysis with Pandas.-Chapter 15: Control Systems Engineering in Python.-Chapter 16: Engineering Data and Databases Using SQLAlchemy.

Über Autor(innen)

Carlos Freitas is an Electrical Engineer with a master’s degree in Computational Systems Applied to Engineering and specializations in Software Engineering and Control Systems. He began his career as an Electromechanical Technician, building a solid foundation in electrical systems, electronics, and industrial automation. His work spans machine automation, industrial systems, and AI applications using Python and TensorFlow. Carlos is currently pursuing a PhD in Electrical Engineering with a focus on Robotics and teaches engineering and technical programs at the Federal Institute of Education in Brazil.