This course is based (but does not depend) on the competencies and knowledge obtained in the previous courses:
The use of the network model for describing and treating complex systems is a huge change of paradigm introduced in this century. This model represents a powerful way of organizing, processing, and interpreting the data plethora generated nowadays as a consequence of the operation or analysis of corporative, technological, or natural systems. Its application to the treatment of social, communication, economic or genomic networks, among others, provides an opportunity for new business models. In addition, this approach offers an increase in the competitiveness and operative capability of corporations, organizations, and government agencies. This course presents the foundations of the network model and the algorithmic techniques that allow generating knowledge from the information extracted from the networks.
Course competences | |
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Code | Description |
BA01 | Ability to solve mathematical problems which can occur in engineering. Skills to apply knowledge about: lineal algebra; integral and differential calculus; numerical methods, numerical algorithms, statistics, and optimization. |
CB03 | Be able to gather and process relevant information (usually within their subject area) to give opinions, including reflections on relevant social, scientific or ethical issues. |
CB04 | Transmit information, ideas, problems and solutions for both specialist and non-specialist audiences. |
CM05 | Ability to acquire, formalise, and represent human knowledge in a computable form for the solution of problems throughout a digital system in any application context, especially the one linked to computational aspects, perception, and behaviour in intelligent frames. |
CO13 | Knowledge and application of the required tools for the storage, process, and access to informational systems, even web based ones. |
INS04 | Problem solving skills by the application of engineering techniques. |
PER01 | Team work abilities. |
SI01 | Ability to integrate information and communiction technology solutions and entrepeneurial process so as to fulfil the needs for information in organisation, allowing them to meet their goals in an effective and efficient manner, providing them with competitive benefits. |
SIS08 | Initiative and entrepreneurial abilities. |
UCLM02 | Ability to use Information and Communication Technologies. |
Course learning outcomes | |
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Description | |
Ability to debate and discuss, in a reasoned manner, the issues and problems involved in the business decision-making process from a quantitative perspective. | |
Ability to analyse the robustness of networked systems such as communication networks or the financial system. | |
Ability to determine and interpret the characteristic structural parameters of networked systems. | |
Selection and management of required algorithms to determine the structure of communities and dynamics of networked systems. | |
Ability to use tools and develop applications and services that process information and provide intelligence to the environment of organisations. | |
Additional outcomes | |
Not established. |
Training Activity | Methodology | Related Competences (only degrees before RD 822/2021) | ECTS | Hours | As | Com | Description | |
Class Attendance (theory) [ON-SITE] | Lectures | BA01 CB03 INS04 SI01 | 0.72 | 18 | N | N | Teaching of the subject matter by lecturer | |
Individual tutoring sessions [ON-SITE] | BA01 CB03 CB04 SIS08 UCLM02 | 0.18 | 4.5 | N | N | Individual or small group tutoring in lecturer¿s office, classroom or laboratory | ||
Study and Exam Preparation [OFF-SITE] | Self-study | BA01 CB03 CM05 CO13 INS04 SI01 SIS08 UCLM02 | 2.1 | 52.5 | N | N | Self-study | |
Other off-site activity [OFF-SITE] | Practical or hands-on activities | BA01 CM05 CO13 INS04 PER01 SI01 SIS08 UCLM02 | 0.6 | 15 | N | N | Lab practical preparation | |
Problem solving and/or case studies [ON-SITE] | Problem solving and exercises | BA01 CB03 CM05 INS04 SI01 SIS08 UCLM02 | 0.6 | 15 | Y | N | Worked example problems and cases resolution by the lecturer and the students | |
Writing of reports or projects [OFF-SITE] | Self-study | BA01 CB03 CB04 CM05 CO13 INS04 SI01 SIS08 UCLM02 | 0.9 | 22.5 | Y | N | Preparation of essays on topics proposed by lecturer | |
Laboratory practice or sessions [ON-SITE] | Practical or hands-on activities | INS04 PER01 SI01 SIS08 UCLM02 | 0.6 | 15 | Y | Y | Realization of practicals in laboratory /computing room | |
Other on-site activities [ON-SITE] | Assessment tests | BA01 CM05 INS04 SI01 SIS08 UCLM02 | 0.3 | 7.5 | Y | Y | Final exam including all topics | |
Total: | 6 | 150 | ||||||
Total credits of in-class work: 2.4 | Total class time hours: 60 | |||||||
Total credits of out of class work: 3.6 | Total hours of out of class work: 90 |
As: Assessable training activity Com: Training activity of compulsory overcoming (It will be essential to overcome both continuous and non-continuous assessment).
Evaluation System | Continuous assessment | Non-continuous evaluation * | Description |
Final test | 50.00% | 50.00% | Compulsory activity that can be retaken (rescheduling) to be carried out within the planned exam dates of the final exam call (convocatoria ordinaria) |
Theoretical papers assessment | 15.00% | 15.00% | Non-compulsory activity that can be retaken. To be carried out before end of teaching period |
Laboratory sessions | 25.00% | 25.00% | Compulsory activity that can be retaken. To be carried out during lab sessions |
Oral presentations assessment | 10.00% | 10.00% | Non-compulsory activity that can be retaken. To be carried out during the theory/lab sessions |
Total: | 100.00% | 100.00% |
Not related to the syllabus/contents | |
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Hours | hours |
General comments about the planning: | The subject is taught in 3 x 1,5 hour sessions per week. The planning can be modified in the event of unforeseen causes. |
Author(s) | Title | Book/Journal | Citv | Publishing house | ISBN | Year | Description | Link | Catálogo biblioteca |
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Albert-László Barabási | Network Science | Cambridge University Press | 978-1107076266 | 2016 | http://networksciencebook.com/ | ||||
Kayhan Erciyes | Complex Networks: An Algorithmic Perspective | CRC Press | ¿ 978-1466571662 | 2014 | |||||
M. E. J. Newman | Networks: An Introduction | Oxford University Press | 978-0198805090 | 2018 |