Competencies and objectives

Provisional information. Pending approval by the Department Council.

 

Course context for academic year 2024-25

Fundamentals of Mathematics in Engineering III is a basic subject in the Civil Engineering Degree. The subject belongs to the first course and will take place in the second semester.

This is a previous requirement for the subject Civil Construction Engineering, which takes part of the syllabus Port and Coastal Engineering, and which is studied in the fourth year (seventh semester).

 

RELATIONSHIP WITH THE SUSTAINABLE DEVELOPMENT GOALS (SDGs):


• SDG 04 - Quality education
• SGD 08 - Decent work and economic growth
• SDG 09 - Industry, innovation and infraestructure



DIGITALIZATION:


• Use of Moodle for organizing teaching materials, planning, and completing and submitting assignments.
• Use of Python to solve mathematical problems in the field of civil engineering, through the application of numerical methods and conducting statistical analysis

 

 

 

Course content (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2024-25

General Competences (CG)

  • CG1 : Capacitat per a la resolució dels problemes matemàtics que puguen plantejar-se en l'enginyeria. Aptitud per a aplicar els coneixements sobre: àlgebra lineal; geometria; geometria diferencial; càlcul diferencial i integral; equacions diferencials i en derivades parcials; mètodes numèrics; algorítmica numèrica; estadística i optimització.
  • CG3 : Coneixements bàsics sobre l'ús i programació dels ordinadors, sistemes operatius, bases de dades i programes informàtics amb aplicació en enginyeria.

 

Competencias Generales (Objetivos)

  • O1 : Capacitación científica-técnica para el ejercicio de la profesión de Ingeniero Técnico de Obras Públicas y conocimiento y ejercicio de las funciones de asesoría, análisis, planificación, diseño, cálculo, proyecto, dirección, construcción, gestión, mantenimiento, conservación y explotación en el ámbito de la Ingeniería Civil.
  • O2 : Comprensión de los múltiples condicionamientos de carácter técnico y legal que se plantean en la construcción de una obra pública, y capacidad para emplear métodos contrastados y tecnologías acreditadas, con la finalidad de conseguir la mayor eficacia en la construcción dentro del respeto por el medio ambiente y la protección de la seguridad y salud de los trabajadores y usuarios de la obra pública.

 

 

 

Learning outcomes (Training objectives)

No data

 

 

Specific objectives stated by the academic staff for academic year 2024-25

1. An understanding of the usefulness and the need for the numeric methods in Civil Engineering.
2. The knowledge of a set of numeric methods for design and calculation in Civil Engineering.
3. The capacity to compare the efficiency of the different numerical methods.
4. The knowledge of the theoretic and practice convergence conditions of the methods (consistence, stability, error).
5. The capacity to analyze and deduce algorithms.
6. The skill using the calculator, computer and software for the resolution of problems by means of numerical methods.
7. The skill in the interpretation, representation and submission of numerical results. The capacity to interpret correctly the results, in relation with the problem that is tried to solve, contrasting with other sources of information.
8. The capacity to discriminate between the aims of a statistical analysis: descriptive statistics or statistical inference.
9. The capacity to distinguish between a statistical population and a sample of that one.
10. The capacity to synthesize and describe a large amount of information selecting the right statistics for the type of variables and to analyze the existing connections between them.
11. The knowledge of the usefulness and the need for the Statistics like a tool in the profession of the engineer.
12. The knowledge of the probabilistic base of the statistical inference.
13. The capacity to estimate unknown parameters of a population from a sample.
14. The knowledge of the principles and applications of the statistical hypothesis testing.
15. The capacity to compare two populations from characteristic and unknown parameters of that ones.
16. The capacity to formulate real problems in statistical terms (parameters estimation, testing hypothesis, etc.) and to apply the statistical inference to solve them.
17. The knowledge of the basic principles and the applicability of techniques relating to the quality control.
18. The knowledge of the general foundations of the more usual probabilistic models.
19. Have a good command of the statistical tables, calculator and statistical packages.

 

 

General

Code: 33508
Lecturer responsible:
SAYOL ESPAÑA, JUAN MANUEL
Credits ECTS: 6,00
Theoretical credits: 0,00
Practical credits: 2,40
Distance-base hours: 3,60

Departments involved

  • Dept: SCIENCE OF COMPUTING AND ARTIFICIAL INTELLIGENCE
    Area: SCIENCE OF COMPUTING AND ARTIFICIAL INTELLIGENCE
    Theoretical credits: 0
    Practical credits: 0
  • Dept: APPLIED MATHEMATICS
    Area: APPLIED MATHEMATICS
    Theoretical credits: 0
    Practical credits: 2,4
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught