OUR EXPERT'S VISION
Angel Luis Aldana
Modern engineering demands tools that integrate precision, efficiency, and versatility. Python has become one of the most powerful languages for technical work thanks to its ability to automate tasks, process data, create simulations, and develop rapid solutions without relying on expensive software.
This course introduces participants to the practical use of Python with an engineering focus, covering everything from programming fundamentals to applied libraries (NumPy, Pandas, Matplotlib). Real-world examples of automating calculations, processing experimental data, and generating technical graphs will be explored.
This results-oriented training will help every engineer incorporate programming into their professional toolkit.
PYTHON FOR ENGINEERS: APPLIED PROGRAMMING
Apply Python to solve real-world problems in engineering and data.
Hours CLASS SESSIONS:
WEEKS:
Minimum TOTAL hours of COMPLETION of the course:
AVAILABILITY:
CURRENT PRICE (€):
NIEX´s value:
AGE (minimum recommended):
ESTIMATED NEXT DATE OF CELEBRATION:
Can the Course be FREE?:
10
8
40
1200
+18
Tailored
Yes, ask us how
Course Objectives
Understand the fundamentals of the Python language and its basic syntax.
Applying Python to technical calculations, data analysis, and simulations.
Develop scripts to automate repetitive tasks.
Visualize engineering data and results using dynamic graphics.
Who is it for?
Engineers, technicians, and STEM students interested in incorporating programming into their professional practice.
Career Opportunities
Automation of technical processes.
Data analysis and visualization in industrial or scientific environments.
Development of customized tools for engineering.
Requirements
Basic knowledge of mathematics and logic. No prior programming experience required.
SUGGESTED COURSE CONTENT AGENDA
Module 1: Introduction to Python and programming fundamentals.
Installation and configuration of environment (Anaconda, VSCode, Jupyter).
Data types, operators, control structures, and functions.
Good practices and coding style in engineering.
Basic exercises: mathematical calculations and automation of repetitive operations.
Module 2: Python as a tool for calculation and numerical analysis.
Introduction to NumPy: creating and manipulating matrices and vectors.
Vector calculus, linear algebra, interpolation, and differential equations.
Real-world applications: dimensioning of structural elements, analysis of materials, strength and energy efficiency.
Practical exercise: create a script to solve a system of technical equations.
Module 3: Analysis and visualization of technical data.
Using Pandas to import, clean, and analyze experimental or sensor data.
Descriptive statistics, correlations, and large data management.
Creating technical graphs with Matplotlib and Seaborn.
Applied exercise: performance analysis of a plant or technical system.
Module 4: Simulation, optimization and advanced automation.
Introduction to SciPy and optimization libraries.
Task automation with scheduled scripts.
Simulations and analysis of engineering scenarios.
Automated report generation and interactive visualization.
Final project: development of a tool in Python to solve a real problem in your specialty (industrial, civil, energy, telecommunications or data).
At the moment you finish this course, you will receive a certificate of completion:
SHARE THIS COURSE
ADD YOUR DATA
CONFIRM YOUR COURSE OF " YOU CAN NOW BOOK IT " OR "IN PREPARATION" .
SELECT WHERE WE SEND YOU THE PAYMENT LINK.
YOU WILL RECEIVE ALL THE COURSE DETAILS (DATES...) AND THE PAYMENT LINK WITH THE DISCOUNT APPLIED.
BOOK YOUR PLACE NOW AND YOU WILL HAVE A DISCOUNT OF UP TO 30%
