Buch, Englisch, 285 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 780 g
ISBN: 978-3-031-57147-3
Verlag: Springer Nature Switzerland
This book introduces computing and programming with undergraduate engineering students in mind. It uses Python (Version 3) as the programming language, chosen for its simplicity, readability, wide applicability and large collection of libraries. After introducing engineering-related Python libraries, such as NumPy, Pandas, Matplotlib, Sci-kit, shows how Python can be used to implement methods common in a wide spectrum of engineering-related problems drawn from (for example): design, control, decision-making, scheduling and planning.
Important features of the book include the following:
- The book contains interactive content for illustration of important concepts, where the user can provide input and by clicking buttons, trace through the steps.
- Each chapter is also accessible as a Jupyter Notebook page and every code piece is executable. This allows the readers to run code examples in chapters immediately, to make changes and gain a better grasp of the concepts presented.
- The coverage of topics is complemented by illustrative examples and exercises.
- For instructors adopting the textbook, a solutions manual is provided at https://sites.google.com/springernature.com/extramaterial/lecturer-material.
Zielgruppe
Lower undergraduate
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmierung: Methoden und Allgemeines
- Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau
- Technische Wissenschaften Bauingenieurwesen Bauingenieurwesen
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
Weitere Infos & Material
1.Computing and Computers.- 2.Programming and Programming Languages.- 3.Representation of Data.- 4.Dive into Python.- 5.Conditional and Repetitive Execution.- 6.Functions.- 7.A Gentle Introduction to Object-Oriented Programming.- 8.File Handling.- 9.Error Handling and Debugging.- 10.Scientific and Engineering Libraries.- 11.An Application:Approximation and Optimization.- 12.An Application:Solving a Simple Regression Problem.- Glossary.- Index.