Artificial Intelligence Seminar

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Credits
3
Types
Elective
Requirements
This subject has not requirements

Department
URV
Mail
This seminar will consist on the description of a research field relevant within Artificial Intelligence by national or international lecturers during one week.

Teachers

Person in charge

  • Antonio Moreno Ribas ( )

Weekly hours

Theory
1.5
Problems
0
Laboratory
0
Guided learning
0
Autonomous learning
3.5

Competences

Technical Competences of each Specialization

Academic

  • CEA7 - Capability to understand the problems, and the solutions to problems in the professional practice of Artificial Intelligence application in business and industry environment.
  • CEA8 - Capability to research in new techniques, methodologies, architectures, services or systems in the area of ??Artificial Intelligence.

Professional

  • CEP2 - Capability to solve the decision making problems from different organizations, integrating intelligent tools.
  • CEP3 - Capacity for applying Artificial Intelligence techniques in technological and industrial environments to improve quality and productivity.
  • CEP4 - Capability to design, write and report about computer science projects in the specific area of ??Artificial Intelligence.

Transversal Competences

Teamwork

  • CT3 - Ability to work as a member of an interdisciplinary team, as a normal member or performing direction tasks, in order to develop projects with pragmatism and sense of responsibility, making commitments taking into account the available resources.

Information literacy

  • CT4 - Capacity for managing the acquisition, the structuring, analysis and visualization of data and information in the field of specialisation, and for critically assessing the results of this management.

Reasoning

  • CT6 - Capability to evaluate and analyze on a reasoned and critical way about situations, projects, proposals, reports and scientific-technical surveys. Capability to argue the reasons that explain or justify such situations, proposals, etc..

Analisis y sintesis

  • CT7 - Capability to analyze and solve complex technical problems.

Objectives

  1. Understand the basic concepts of a relevant area within AI and its relationship with the business world.
    Related competences: CT4, CEA7, CEP2, CEP3,
  2. Solve in an effective way a problem related to the field presented in the seminar.
    Related competences: CT3, CT6, CT7, CEA8, CEP4,

Contents

  1. Theoretical issues
    Presentation of an advanced research topic in the AI field.
  2. Practical content
    Resolution or analysis of a specific problem within the field presented in the seminar.

Activities

Lectures

Presentation of the theoretical content of the seminar.
Theory
22.5
Problems
0
Laboratory
0
Guided learning
0
Autonomous learning
52.5
  • Theory: Invited lectures at the seminar.
  • Autonomous learning: Autonomous student work: state-of-the-art analysis, paper review, elaboration of written report.
Objectives: 1
Contents:

Teaching methodology

The following teaching methodologies will be employed:

* Lectures.
* Participative sessions.
* Team work.
* Autonomous work.

Evaluation methodology

The evaluation will be based on the elaboration of a written report,
individually or in pairs of students. In this document students will be asked to
review some current scientific papers on the topic covered in the seminar and
to provide a critical assessment of the main AI techniques used in the field.

Bibliografy

Basic:

Complementary:

Web links

Previous capacities

Knowledge of the basic concepts in AI.