Competencies and objectives

 

Course context for academic year 2024-25

This course provides the knowledge and skills on architectures and high-performance computing to implement AI-based research and applications.
research and carry out AI-based applications. It covers  modern architectures that take into account the computing resources of the  computing resources massively parallel computing resources, new trends in advanced processing and cloud computing.
This knowledge will facilitate the development of efficient algorithms based on the architectural  based on the architectural characteristics of the systems used.

 

 

Course content (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2024-25

Transversal Competences

  • CT1 : Be able to lead projects related to artificial intelligence, as well as to manage work teams.
  • CT2 : Demonstrate computer and information skills in the field of artificial intelligence.
  • CT3 : Show oral and written communication skills.

 

General Competences

  • CG1 : Apply the knowledge acquired to real problems related to artificial intelligence.
  • CG10 : Be able to use engineering principles and modern computer technologies to research, design and implement new applications of artificial intelligence,
  • CG5 : Know how to manage the available information and resources related to artificial intelligence.
  • CG7 : To be able to adapt to the constant evolution of the discipline and to understand and apply new technical and scientific developments related to artificial intelligence.
  • CG8 : Knowing how to plan, design, develop, implement and maintain products, applications and services related to artificial intelligence, taking into account technical, economic and efficiency aspects.

 

Specific Competences

  • CE18 : Identify and apply advanced computing technologies and architectures for the design of artificial intelligence solutions.
  • CE19 : Know and manage cloud-based platforms and services for the deployment of artificial intelligence systems and applications.

 

Basic Competences

  • CB10 : That students possess the learning skills that allow them to continue studying in a way that will be largely self-directed or autonomous.
  • CB6 : Possess and understand knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context
  • CB7 : That students know how to apply the knowledge acquired and their ability to solve problems in new or little-known environments within broader (or multidisciplinary) contexts related to their area of ¿¿study
  • CB8 : Students are able to integrate knowledge and deal with the complexity of making judgements on the basis of incomplete or limited information, including reflections on the social and ethical responsibilities associated with information which, while incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of their knowledge and judgements.
  • CB9 : Students are able to communicate their conclusions and the ultimate knowledge and rationale behind them to specialist and non-specialist audiences in a clear and unambiguous way.

 

 

 

Learning outcomes (Training objectives)

- Know the technological alternatives for the processing and management and storage of AI applications.

- Define the technological requirements for running applications on different platforms depending on the scope of application for a given design.

- Evaluate the difference in performance between different platforms and technologies to be able to recommend a solution.

- Model solutions to be able to use different platforms.

 

 

Specific objectives stated by the academic staff for academic year 2024-25

To understand the main elements and architectures of multi-computer and multi-processor systems.
To know advanced distributed systems and architectures.
To know how to use architectures based on specific-purpose processors.

 

 

General

Code: 43506
Lecturer responsible:
García Rodríguez, Jose
Credits ECTS: 3,00
Theoretical credits: 0,60
Practical credits: 0,60
Distance-base hours: 1,80

Departments involved

  • Dept: INFORMATION TECHNOLOGY AND COMPUTING
    Area: COMPUTER ARCHITECTURE
    Theoretical credits: 0,6
    Practical credits: 0,6
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught