Artificial Intelligence Seminar

Credits
3
Types
Elective
Requirements
This subject has not requirements , but it has got previous capacities
Department
CS;URV
Web
https://campusvirtual.urv.cat
Mail
antonio.moreno@urv.cat
This seminar will consist on the description of a relevant research field in Artificial Intelligence by national/international lecturers during one week (usually in May). The topic of the seminar is different every academic course.

Teachers

Person in charge

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 content
      Presentation of an advanced research topic in the AI field.
    2. Practical content
      Solve or analyze a specific problem within the field presented in the seminar.

    Activities

    Activity Evaluation act


    Lectures

    Presentation of the theoretical content of the seminar.
    • 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:
    Theory
    22.5h
    Problems
    0h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    52.5h

    Practical component of the seminar

    Study of the state of the art in the seminar's topic or completion of exercises/problems.
    Objectives: 2
    Week: 1
    Theory
    0h
    Problems
    0h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    0h

    Teaching methodology

    The following teaching methodologies will be employed:

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

    Evaluation methodology

    The evaluation will be based on a written report, to be made individually or in pairs
    (depending on the number of enrolled students), where students will show that they have understood
    the topics discussed in the seminar and they are able to analyze their applicability in a specific problem.

    Bibliography

    Basic

    Complementary

    Web links

    Previous capacities

    Knowledge of the basic concepts in AI. It is not necessary to have previous knowledge on the topic of the seminar.