Checking date: 19/05/2022


Course: 2022/2023

Discrete mathematics
(16489)
Study: Bachelor in Data Science and Engineering (350)


Coordinating teacher: MORO CARREÑO, JULIO

Department assigned to the subject: Department of Mathematics

Type: Basic Core
ECTS Credits: 6.0 ECTS

Course:
Semester:

Branch of knowledge: Engineering and Architecture



Requirements (Subjects that are assumed to be known)
Calculus I and II, and Linear Algebra
Skills and learning outcomes
Description of contents: programme
1. Arithmetic 1.1 Integers 1.2 Division algorithm 1.3 Largest common divisor: Euclid's algorithm 1.4 Prime numbers and the Fundamental Theorem of Arithmetic 1.5 Diophantine equations 1.6 Congruences: modular arithmetic 2. Elementary set theory 2.1 Basic notions 2.2 Set operations and properties 2.3 Functions 2.4 Relations: equivalence and order 2.5 Cardinality 3. Combinatorics 3.1 Elementary counting rules: sum and product 3.2 Pigeon-hole principle 3.3 Permutations and combinations 3.4 Binomial coefficients 3.5 Principle of inclusion and exclusion 3.6 Derangements 3.7 Generating functions 3.8 Partitions 3.9 Recurrences 4. Introduction to groups 4.1 Law of composition 4.2 Groups and subgroups 4.3 Homomorphisms and isomorphisms 4.4 Cyclic groups 4.5 Cosets, Lagrange's theorem, and quotient groups 4.6 Applications to cryptography 5. Fundamentals of graph theory 5.1 Definitions and examples 5.2 Matrix representations 5.3 Eulerian and Hamiltonian graphs 5.4 Trees 5.5 Optimisation and matching 5.6 Planar graphs 5.7 Directed graphs 5.8 Networks
Learning activities and methodology
AF1: THEORETICAL AND PRACTICAL LECTURES. These are meant to provide the students the basic knowledge of the topic. They will be provided classroom notes as well as reference textbooks to help them follow the lectures and work them through. Exercises and problems will be solved in class, and midterm exams will be performed to test progress. AF3: PERSONAL WORK AND WORK IN GROUPS. AF9: FINAL EXAM. Overall evaluation of the students' knowledge, skills, and abilities learn through the course. MD1: THEORY CLASS. The teacher will lecture, with the help of computer and audiovisual media, about he main topics of the subject. Materials and biblography will be provided to supplement these lectures. MD2: PRACTICAL CLASS. Practical exercises and problems will be solved, either individually or in groups. MD3: TUTORSHIPS. The student will received assistance by the teacher about difficult matters of the topic, either individually or in groups.
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40
Calendar of Continuous assessment
Basic Bibliography
  • K.H. Rosen. Discrete Mathematics and Its Applications, 7th ed.. McGraw-Hill. 2007
  • N. Biggs. Discrete Mathematics, 2nd ed.. Oxford University Press. 2003
  • R.P. Grimaldi. Discrete and Combinatorial Mathematics: An Applied Introduction, 5th ed.. Addison Wesley. 2004
Additional Bibliography
  • M. E. J. Newman. Networks: An Introduction. Oxford University Press. 2010
  • N. C. Carter. Visual Group Theory. Mathematical Association of America, Inc.. 2009
  • R. J. Wilson. Introduction to Graph Theory, 4th ed.. Addison-Wesley. 1996
  • R. Sedgewick, P. Flajolet. An introduction to the analysis of algorithms, 2nd ed.. Addison-Wesley. 2013
Recursos electrónicosElectronic Resources *
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The course syllabus may change due academic events or other reasons.