Identifying Data 2020/21
Subject (*) Algebra Code 614G01010
Study programme
Grao en Enxeñaría Informática
Descriptors Cycle Period Year Type Credits
Graduate 2nd four-month period
First Basic training 6
Language
Spanish
English
Teaching method Hybrid
Prerequisites
Department Ciencias da Computación e Tecnoloxías da Información
Computación
Coordinador
Vieites Rodriguez, Ana Maria
E-mail
ana.vieites@udc.es
Lecturers
Aguado Martin, Maria Felicidad
Barja Pérez, José María
Costoya Ramos, Maria Cristina
Doncel Juarez, Jose Luis
Perez Vega, Gilberto
Souto Salorio, Maria Jose
Suárez Canedo, Emilio José
Vidal Martin, Concepcion
Vieites Rodriguez, Ana Maria
E-mail
felicidad.aguado@udc.es
j.m.barja@udc.es
cristina.costoya@udc.es
jose.luis.doncel@udc.es
gilberto.pvega@udc.es
maria.souto.salorio@udc.es
emilio.scanedo@udc.es
concepcion.vidalm@udc.es
ana.vieites@udc.es
Web http://campusvirtual.udc.es/moodle
General description A materia de Álxebra é unha materia correspondente ó segundo cuadrimestre do primeiro curso da titulación de Grao en Enxeñaría Informática. Pertence ó módulo de Formación Básica na rama de Enxeñaría e Arquitectura. Nesta materia débense adquirir os hábitos de abstracción e rigor necesarios no ámbito profesional dun informático. Os conceptos que se estudan son básicos para o desenrolo doutras materias máis especificas da titulación; por exemplo, Computación Gráfica, Visión Artificial, Lexislación e Seguridade Informática, Procesamento dixital da Información, Redes.

O carácter dos estudos e as necesidades de formación dos estudantes do Grao en Enxeñaría Informática aconsella un enfoque computacional da álxebra, por iso, porase especial énfase nos conceptos de álxebra que se empregan en teoría de computación, destacando o enfoque algorítmico nos métodos.
Contingency plan 1. Modificacións nos contidos
Os contidos non se modificarán a non ser que, por motivos de falta de tempo, estos teñan que ser reducidos; neste caso os alumnos serán informados a través das plataformas oficiais (Moodle, Teams).


2. Metodoloxías
*Metodoloxías docentes que se manteñen


Sesión maxistral: A través das plataformas virtuais da Universidade, o alumno segue a recibir as notas elaboradas para as clases teóricas presenciais de cada tema.

Prácticas de laboratorio: A través das plataformas virtuais da Universidade, o alumno dispón dos boletíns de exercicios propostos que inclúen as solucións.

Aprendizaxe colaborativa: debido á falta da presencialidade, o alumno pode formular as súas dúbidas ó profesor sobre os conceptos e exercicios, a través das plataformas oficiais.

*Metodoloxías docentes que se modifican

Sesión maxistral: Nos grupos de docencia presencial, pasan a combinarse as clases asíncronas (vía Moodle o alumno ten acceso a vídeos explicativos sobre os conceptos máis complicados da materia, seguidos de boletíns complementarios de exercicios onde o alumno traballa exemplos similares ós dos boletíns) e clases síncronas (a través da plataforma Teams; proporcionándose, ó final de cada sesión o contenido das mesas).

Proba obxectiva: Aínda que se mantén, elimínase a puntuación mínima e realizarase a través das plataformas virtuais oficiais da Universidade. Toda vez que esta proba constitúe o 80% da nota, se as condicións o permiten, dividirase o contido da materia impartida en dúas partes e farase unha proba de cada unha delas (a segunda delas farase na data destinada á proba final).

Prácticas de laboratorio: As clases prácticas son síncronas e asíncronas a través da plataforma Teams. Os alumnos terán acceso ós boletíns de exercicios correspondentes. Nos boletíns propostos incluiránse tódalas solucións detalladas.

3. Mecanismos de atención personalizada ó alumnado

Cada grupo de prácticas terá atención semanal a través da plataforma virtual Teams. Asemesmo o profesor poderá programar sesións de titorías cos alumnos de cara á resolver dúbidas de carácter individual.

4. Modificacións na avaliación: A avaliación pasa a ser sumativa e sen mínimos.

*Observacións de avaliación.
Non se pide mínimo en ningunha das metodoloxías para aprobar a asignatura pois trátase dunha avaliación sumativa
Na primeira oportunidade, cada unha das probas nas que se divide o total da materia, terá un valor do 40%.

Para aprobar a materia o alumno deberá obter 5 puntos ou mais como nota total.
Os alumnos que non superen a materia na primeira oportunidade, terán que presentarse a unha única proba para recuperar a porcentaxe da nota final correspondente à proba final presencial (80%).

5. Modificacións da bibliografía ou webgrafía

Non se modifica porque existen versións pdf on line, aínda que sexan edicións anteriores ás que aparecen na bibliografía, da maioría das obras que forman a bibliografía básica.

Study programme competencies
Code Study programme competences
A1 Capacidade para a resolución dos problemas matemáticos que se poden presentar na enxeñaría. Aptitude para aplicar os coñecementos sobre: álxebra linear; cálculo diferencial e integral; métodos numéricos; algorítmica numérica; estatística e optimización.
A3 Capacidade para comprender e dominar os conceptos básicos de matemática discreta, lóxica, algorítmica e complexidade computacional e a súa aplicación para a resolución de problemas propios da enxeñaría.
B3 Capacidade de análise e síntese
B6 Toma de decisións
C1 Expresarse correctamente, tanto de forma oral coma escrita, nas linguas oficiais da comunidade autónoma.
C6 Valorar criticamente o coñecemento, a tecnoloxía e a información dispoñible para resolver os problemas cos que deben enfrontarse.
C7 Asumir como profesional e cidadán a importancia da aprendizaxe ao longo da vida.

Learning aims
Learning outcomes Study programme competences
Acquire basic concepts from Elementary Number Theory. A1
A3
Interpret and apply the acquired knowledge from Elementary Number Theory to Cryptography. A1
A3
B3
Know some basic concepts of Linear Algebra: systems of linear equations, vectorial spaces, matrices and linear maps. A1
Use Linear Algebra as a tool for modeling and solving processes related to computer science. A1
B6
C6
Know the definitions and basic principles from Coding Theory related to Linear Algebra. A1
Simulate coding and decoding processes using matricial techniques. A1
B6
C6
Learn how to use mathematical language in a proper way to express ideas. A1
C1
Develop the capacities of abstraction, concretion, concision, imagination, intuition, reasoning, criticism, objectivity, synthesis and accuracy; put all of them in practice either in the academic or the professional life for solving problems successfully. B3
C7
Apply basic concepts from the subject and relate to algorithmic and computational concepts in the light of the mathematical ones. A1
C6
Acquire tools and skills for solving problems in a proper way. Express and interprete results in a rigorous way. Check the result and, in case of any incongruence, revise the process to detect the error. A1
B6
C1
C7

Contents
Topic Sub-topic

Chapter 1: Modular arithmetic: application to Cryptography.
Basic concepts from elementary number theory. Euclides' algorithm. Prime numbers. Linear diophantine equations. Congruences. Modular arithmetic.
Definition of cryptosystem. Classical cryptography. Symmetrical and asymmetrical cryptography. Examples of cryptosystems.
Numeration systems. Divisibility criteria.
Chapter 2: Systems of Linear Equations, Matrices and Determinants. Definition and properties of systems of linear equations. Echelon row form of system. Gauss method. Matrices. Operations with matrices. Invertible matrix. Determinant of a square matrix, properties. Cramer's rule.
Chapter 3: Vector Spaces. Definition and properties of a vector space. Bases and coordinates. Dimension. Rank of a set of vectors and matrix rank. Computation of the rank. Change of basis. Rouché-Frobenius theorem.
Chapter 4. Linear maps. Definición e propiedades das aplicacions lineais. Núcleo e imaxe de unha aplicación lineal. Matriz asociada a unha aplicación lineal. Teorema da dimensión.

Definition and properties of linear maps. Kernel and image of a linear map. Matrix associated to a linear map. Dimension theorem.
Chapter 5. Linear Codes Definition of linear codes. Parameters of a linear code. Hamming distance and Hamming weight. Generator matrix and parity-check matrix of a code. Error correction in linear codes. Binary Hamming codes.

Planning
Methodologies / tests Competencies Ordinary class hours Student’s personal work hours Total hours
Guest lecture / keynote speech A1 A3 C6 C7 30 45 75
Laboratory practice A1 B3 B6 C1 C6 20 30 50
Objective test A1 B3 C1 3 0 3
Collaborative learning A1 B3 C1 C7 6 11 17
 
Personalized attention 5 0 5
 
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies Description
Guest lecture / keynote speech The chief means of communication for this course will be the platform Moodle. Students are expected to check this for up-to-date assignments-including material separate from the given at the blackboard-and announcements. Over the semester we will study many topics that form a central part of the language of modern science. Weekly problem sets with a mix of exercices will be given. These include problems requiring abstraction, understanding and/or synthesis of various concepts. In many ways, these constitue the heart of the course; rigor in their completion often yields the greatest understanding.

We want the student to leave the course not only with computational ability, but with the ability to use these notions in their natural scientific contexts, and with an appreciation of their mathematical power.
Laboratory practice The laboratory work is the focal point of learning. A series of exercises related to the theoretical contents explained in the theoretical classes will be given to students at the beginning of every chapter. It ensures that:

I) students work closely with the teacher helping them to grow in confidence, to develop their skills in analysis, and to encourage them to reinforce the learning of theoretical concepts through the resolution of the exercises.

II) students gain capacity of abstraction and understanding.

A typical laboratory practice is a 2-hour class, with small groups of students, discussing the resolution of the exercises. It gives students the chance to interact directly with teachers, to exchange ideas and argue between them, to ask questions, and of course, to learn through the discussion.

Technology can play an important role in the learning of mathematics, and as such, graphing and scientific calculators are permitted for class and homework, though they will not be permitted on tests and quizzes, and thus it is emphasized that students learn not to rely on them. Subject to availability, some exercises may be designed to be solved with computers.


Objective test Realizarase un exame escrito que consistirá nunha colección de cuestións teóricas e/ou de problemas (do mesmo tipo que os propostos nos seminarios(TGR) e nos boletíns de exercicios).
Collaborative learning Collaboration is encouraged, for home and class assignments; however, all submitted assignments must be written up independently and represent the student’s own work and understanding.

Personalized attention
Methodologies
Guest lecture / keynote speech
Laboratory practice
Collaborative learning
Description
The studens have the possibility to revise the qualification obtained in the written final test, proving that this is adjusted to the criteria of evaluation established.

Likewise, the evaluations of the answers to the questions and exercises formulated during the course, with the indications adequate in order to correct the errors and/or improve the answers with a view to a more solid formation, will justify.

In the sessions in reduced groups, the doubts formulated by the students are solved in an individualized way, especially when they are common to several of them or illustrate an interesting case. If the question is more particular or does completely not remain solved for some pupil, it would be treated in the hours of individualized tuition.

Students registered to partial time: Depending on the particularities of every specific case and the possibilities of the teaching staff put in charge of the group to the that it is a pupil registered in time partial assigned, the tests of the continuous evaluation will be adjusted so that this pupil can obtain the same qualification as a pupil of ordinary registration.

Assessment
Methodologies Competencies Description Qualification
Laboratory practice A1 B3 B6 C1 C6 This section will consist of, at least, 2 structured or problem-solving questions based on the different topics, similar to exercises from the weekly 2-hour session classes. Correct answers as well as the presentation and clarity of the exposition will be valued.

A participative attitude of the student in the resolution of the proposed exercises during the sessions will also be positively valued.

20
Objective test A1 B3 C1 Ó final do cuatrimestre realizarase unha proba escrita que inclúe:
- Preguntas curtas que permitan valorar se o alumno comprendeu os conceptos teóricos básicos.
- Problemas cun grao de dificultade semellante aos realizados na aula e aos presentados nas coleccións de exercicios propostos.
Avaliarase o dominio dos conceptos teóricos da materia, a comprensión dos mesmos e a súa aplicación na resolución de exercicios. Asimesmo, valorarase a claridade, a orde e a presentación dos resultados expostos.

A presentación á proba final do curso supón que o estudante completou o proceso de avaliación continua.

Hai que obter máis de 3 puntos, dos 8 posibles, na proba obxectiva para sumar a ésta a cualificación de evaluación continua (a cualificación final, neste caso, obténse sumando a cualificación da proba obxectiva e a da avaliación continua). Noutro caso, a cualificación final do alumno é, soamente, a nota da proba obxectiva.
80
 
Assessment comments
Evaluation
of the student registered in time partial:
Depending on the
particularities of every specific case and the possibilities of the
teaching staff put in charge of the group to the that it is a student
registered in time partial assigned, the tests of the continuous
evaluation will be adjusted so that this student can obtain the same
qualification as a student of ordinary registration.

In the
opportunity advanced to December,
the examination will be qualified
on ten points, being necessary to obtain at least one five to approve
the matter.


Sources of information
Basic Grossman, S. I. (1996). Álgebra lineal con aplicaciones. McGraw-Hill Interamericana México.
Merino, L. y Santos, E. (2006). Álgebra Lineal con Métodos Elementales. Thomson.
Lay, D. C. (2007). Algebra Lineal y sus Aplicaciones. Prentice Hall
Rosen, K. H. (2003). Discrete Mathematics and Its Applications. McGraw-Hill
Grossman, S. I. (1994). Elementary Linear Algebra with Applications. Wiley
Cameron, P. J. (1998). Introduction to Algebra. Oxford University Press, Oxford.
Lay, D. C. (2011). Linear Algebra and Its Applications. Pearson
Biggs, N. L. (1994). Matemática Discreta. Madrid, Vicens Vives.
Rosen, K. H. (2004). Matemática Discreta y sus aplicaciones. McGraw-Hill Interamericana.

Complementary Nakos, G. y Joyner, D. (1999). Álgebra lineal con aplicaciones. Thomson.
Hernández, E. (1994). Álgebra y Geometría. Addison-Wesley.
Lidl, R. y Pilz, G. (1998). Applied Abstract Algebra. Nueva York, Springer.
Rojo, J. y Martín, I. (2005). Ejercicios y problemas de Álgebra Lineal. McGraw-Hill.
Torrecilla Jover, B. (1999). Fermat. El Mago de los Números. Nivola.
Van Lint, J. H. (1999). Introduction to Coding Theory. Berlín, Springer.
Nakos, G. y Joyner, D. (1998). Linear Algebra with Applications. Brooks Cole Publising
Singh, S. (2000). Los Códigos Secretos. Debate


Recommendations
Subjects that it is recommended to have taken before
Discrete Mathematics/614G01004

Subjects that are recommended to be taken simultaneously

Subjects that continue the syllabus

Other comments


(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.