Abstract:

The Universitat Jaume I of Castellón (Spain) offers a Master's Degree in Intelligent Systems. It consists of seven modules, each one integrating different topics related to Computer Science. One of these modules refers to the design, development and implementation of pattern recognition and computer vision systems. The objective of this module is to supply students with a solid scientific and technological knowledge base in the areas of pattern recognition and computer vision, both from a professional and a research standpoint. In order to achieve a general and complete perspective of these areas, the module is composed of two compulsory and three optional courses.

From the different courses that integrate the aforementioned module, Pattern Recognition and Machine Learning are two strongly related subjects that can be considered as the foundation for facing many real-life problems, not only in computer vision, but also in a large variety of other application fields such as web and data mining, natural language processing, bioinformatics, big data analytics, manufacturing, computer-aided medical diagnosis, etc. The Pattern Recognition course is an introductory course that covers the basic theory, algorithms, and applications; it intends to provide students with an overview of the core principles of this subject, and introduces a set of techniques that can be employed to construct a non-specific pattern recognition system within the statistical paradigm. On the other hand, the Machine Learning course expands the fundamentals presented in the Pattern Recognition course and has an intense focus on understanding advanced and more complex methods for learning and classification, such as decision trees, neural networks, support vector machines and ensembles, as well as shows how to implement several popular algorithms from scratch.

This paper concentrates on the Pattern Recognition course because of its relevance for developing a high-standard curriculum in numerous scientific areas, and more specifically in pattern recognition. In particular, we will discuss the methodological training framework adopted by the lecturers in the Universitat Jaume I, while describing the objectives of this course, its target competencies and contents, the assessment process, and the basic resources and tools used for introducing the subjects of such course.

Keywords:

Intelligent Systems, Pattern Recognition, Master's Degree, learning experiences.