Competencies and objectives
- Course context for academic year 2020-21
- Course content (verified by ANECA in official undergraduate and Master’s degrees)
- Learning outcomes (Training objectives)
- Specific objectives stated by the academic staff for academic year 2020-21
Course context for academic year 2020-21
International scientific associations such as IEEE Institute of Electrical and Electronics Engineer) y ACM (Association for Computing Machinery) promoted by profesionals of Computer Science and Computer Engineering have selected the following mathematical topics: Logic, Discrete Maths, Graph Theory, Statistics, etc., as essential tools for any graduate in Computer Science, since they cover basic aspects of both hardware and software understanding and design.
In Maths I, included in the first course of Degree in Computer Engineering as a basic subject, we cover both Computational Logic and Linear Algebra (matrix theory).
Logic contributes to develop mathematical reasoning for solving problems in engineering.
Linear Algebra covers matrix theory, including solving linear systems through numerical methods addressed to find fast and convergent solutions.
Course content (verified by ANECA in official undergraduate and Master’s degrees)
General Competences (CG)
- CG1 : Capacity to resolve mathematical problems arising in engineering. Ability to apply knowledge of: linear algebra, differential and integral calculus, numerical methods, numerical algorithms, statistics and optimisation.
- CG3 : Capacity to understand and master the basic concepts of discrete mathematics, logic, algorithms and computational complexity and their application to solve problems related to engineering.
Learning outcomes (Training objectives)
No data
Specific objectives stated by the academic staff for academic year 2020-21
- Know the formal system of First Order Logic, because it is a basic knowledge mandatory to be able to optimize algorithm and program development.
- Formulate and demonstrate validity of deductive arguments through logical deductive processes.
- Learn and master main concepts from Linear Algebra: solving methods for Linear Equation Systems, matrices, Rn subspaces, determinants, eigen vectors and eigen values.
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