| Competences |
| Type A | Code | Competences Specific |
| A1 | Integrate the fundamental technology, applications, services and systems of Computer Security and Artificial Intelligence,in a broader, multidisciplinary context. | |
| A7 | Understand and apply advanced knowledge of high performance computing and numerical or computational problems related to artificial intelligence neural networks and evolutionary systems methods. | |
| G2 | Perform mathematical modelling, calculation and simulation in company technology and engineering centres, particularly in tasks of research, development and innovation in the areas of Computer Security and Artificial Intelligence | |
| Type B | Code | Competences Transversal |
| CT2 | Forming opinions on the basis of the efficient management and use of information | |
| CT3 | Solve complex problems critically, creatively and innovatively in multidisciplinary contexts. | |
| Type C | Code | Competences Nuclear |
| Learning outcomes |
| Type A | Code | Learning outcomes |
| A1 |
Analyse the problems and their causes from a global focus in the medium and long term. | |
| A7 |
Know the main characteristics of the complex network theory. Know the structural properties of complex networks. Know how to implement complex network models. Know how to use network community detection methods. Know how to solve dynamic problems in complex networks. Es familiaritza amb la recerca, comprensió i utilització d'articles d'investigació en llengua estrangera. | |
| G2 |
Apply the techniques learned in a specific context. | |
| Type B | Code | Learning outcomes |
| CT2 |
Master the tools for managing their own identity and activities in a digital environment. Search for and find information autonomously using criteria of importance, reliability and relevance, which is useful for creating knowledge Organise information with appropriate tools (online and face-to-face) so that it can be updated, retrieved and processed for re-use in future projects. Produce information with tools and formats appropriate to the communicative situation and with complete honesty. Use IT to share and exchange the results of academic and scientific projects in interdisciplinary contexts that seek knowledge transfer. | |
| CT3 |
Recognise the situation as a problem in a multidisciplinary, research or professional environment, and take an active part in finding a solution. Follow a systematic method with an overall approach to divide a complex problem into parts and identify the causes by applying scientific and professional knowledge. Design a new solution by using all the resources necessary and available to cope with the problem. Draw up a realistic model that specifies all the aspects of the solution proposed. Assess the model proposed by contrasting it with the real context of application, find shortcomings and suggest improvements. | |
| Type C | Code | Learning outcomes |
| Contents |
| Topic | Sub-topic |
| Structural properties of complex networks |
Introduction to complex networks Real networks examples Classification of networks Metrics on networks |
| Models of complex networks | Erdos-Renyi model Barabasi-Albert preferential attachment Configuration model Watts-Strogatz small-world model |
| Mesoscopic description of complex networks | Community structure in complex networks Community detection algorithms Multiple resolution of community structure in networks |
| Dynamics on networks | Synchronization in complex networks Epidemic spreading in complex networks Other dynamics: percolation, evolutionary games, diffusion, etc. |
| Planning |
| Methodologies :: Tests | ||||||||||
| Competences | (*) Class hours |
Hours outside the classroom |
(**) Total hours | |||||||
| Introductory activities |
|
1 | 0 | 1 | ||||||
| Lecture |
|
22 | 18 | 40 | ||||||
| IT-based practicals in computer rooms |
|
6 | 12 | 18 | ||||||
| IT-based practicals |
|
6 | 80 | 86 | ||||||
| Personal attention |
|
1 | 0 | 1 | ||||||
| Oral tests |
|
2 | 2 | 4 | ||||||
| (*) On e-learning, hours of virtual attendance of the teacher. (**) The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | ||||||||||
| Methodologies |
| Description | |
| Introductory activities | Introduction to the course and its contents |
| Lecture | Contents exposition |
| IT-based practicals in computer rooms | Tools for the developent of solutions and the practical resolution of problems |
| IT-based practicals | Practical exercises to attain experience and consolidate the theoretical knowledge |
| Personal attention | Personal tuition, both in person or through telematic means |
| Personalized attention |
| Description |
|
Resolution of doubts about contents and practical exercises. It will be performed either at the professors' offices (in the reserved hours, or previously arranged meeting), or by telematic means (e-mail, virtual campus, videoconference, etc.) |
| Assessment |
| Methodologies | Competences | Description | Weight | ||||||
| IT-based practicals |
|
Between four and five practical works | 90% | ||||||
| Oral tests |
|
Exposition of a work | 10% | ||||||
| Others |
| Other comments and second exam session | |||
|
Second call: practical exercises 100% |
|||
| Sources of information |
| Basic |
Newman, M.E.J., Networks: An Introduction, 2nd ed., Oxford University Press, 2018 |
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| Complementary | |||||||||
| Recommendations |
(*)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.