23
Σαβ, Σεπ
  • Κωδικός / Course Code: COS695
  • ECTS: 5
  • Τρόποι Αξιολόγησης / Assessment:

    A student is graded "Success" if he / she fulfills the following obligations on the electronic platform of the EU funded Project “2BeConnected”:

    • Satisfactory completion of the required actions (weekly work program, student evaluation, final report, etc.)
    • Positive evaluation by the host organization
    • Positive evaluation both by the Academic Industry Placement Supervisor on the electronic platform of the EU funded Project “2BeConnected” and the Liaison Officers of the Open University of Cyprus.

    The student will be graded "Failure" if he / she does not fulfill the above obligations satisfactorily.

  • Διάρκεια Φοίτησης/ Length of Study: Εξαμηνιαία (εαρινό ή χειμερινό)/ Semi-annual (Fall or Spring)
  • Επίπεδο Σπουδών/ Level: Μεταπτυχιακό/ Postgraduate
  • Προαπαιτούμενα/ Prerequisites: Pre-requisite Modules COS511 Introduction to Cognitive Psychology COS512 Introduction to Artificial Intelligence COS513 Computational Intelligent Systems
  • Αναλυτική πληροφόρηση: COS695_Cognitive_Systems.pdf

With the successful completion of this module, the students should be able to:

  • Co-operate effectively with their co-workers.
  • Solve any problems presented/assigned to them, successfully.
  • Communicate their ideas, problems and issues related to their work to their co-workers and managers.
  • Take initiatives and make suggestions on work-related topics.
  • Perform their duties with responsibility and diligence.
  • Demonstrate a professional profile at work.
  • Associate their academic knowledge with their work area.
  • Κωδικός / Course Code: COS695
  • ECTS: 5
  • Τρόποι Αξιολόγησης / Assessment:

    A student is graded "Success" if he / she fulfills the following obligations on the electronic platform of the EU funded Project “2BeConnected”:

    • Satisfactory completion of the required actions (weekly work program, student evaluation, final report, etc.)
    • Positive evaluation by the host organization
    • Positive evaluation both by the Academic Industry Placement Supervisor on the electronic platform of the EU funded Project “2BeConnected” and the Liaison Officers of the Open University of Cyprus.

    The student will be graded "Failure" if he / she does not fulfill the above obligations satisfactorily.

  • Διάρκεια Φοίτησης/ Length of Study: Εξαμηνιαία (εαρινό ή χειμερινό)/ Semi-annual (Fall or Spring)
  • Επίπεδο Σπουδών/ Level: Μεταπτυχιακό/ Postgraduate
  • Προαπαιτούμενα/ Prerequisites: Pre-requisite Modules COS695 Industry Placement
  • Αναλυτική πληροφόρηση: COS696_Cognitive_Systems.pdf

With the successful completion of this module, the students should be able to:

  • Co-operate effectively with their co-workers.
  • Solve any problems presented/assigned to them, successfully.
  • Communicate their ideas, problems and issues related to their work to their co-workers and managers.
  • Take initiatives and make suggestions on work-related topics.
  • Perform their duties with responsibility and diligence.
  • Demonstrate a professional profile at work.
  • Associate their academic knowledge with their work area.
  • Κωδικός / Course Code: COS701B
  • ECTS: 20
  • Τρόποι Αξιολόγησης / Assessment:

    -

  • Διάρκεια Φοίτησης/ Length of Study: Εξαμηνιαία (εαρινό ή χειμερινό)/ Semi-annual (Fall or Spring)
  • Κόστος/ Tuition Fees: 900 euro
  • Επίπεδο Σπουδών/ Level: Μεταπτυχιακό/ Postgraduate
The Master Thesis should reflect autonomous study on behalf of the student, and should deal with a scientific topic of research interest in the area of cognitive systems. Emphasis can be on the psychological or computational side of things. Key are the elements of innovation and scientific quality of the resulting research, contributing new knowledge to the scientific community.
  • Κωδικός / Course Code: COS701A
  • ECTS: 10
  • Τρόποι Αξιολόγησης / Assessment:

    -

  • Διάρκεια Φοίτησης/ Length of Study: Εξαμηνιαία (εαρινό ή χειμερινό)/ Semi-annual (Fall or Spring)
  • Κόστος/ Tuition Fees: 450 euro
  • Επίπεδο Σπουδών/ Level: Μεταπτυχιακό/ Postgraduate
The Master Thesis should reflect autonomous study on behalf of the student, and should deal with a scientific topic of research interest in the area of cognitive systems. Emphasis can be on the psychological or computational side of things. Key are the elements of innovation and scientific quality of the resulting research, contributing new knowledge to the scientific community.
  • Κωδικός / Course Code: COS624
  • ECTS: 10
  • Τρόποι Αξιολόγησης / Assessment:

    -

  • Διάρκεια Φοίτησης/ Length of Study: Εξαμηνιαία (χειμερινό) / Semi-annual (fall)
  • Κόστος/ Tuition Fees: 450 euro
  • Επίπεδο Σπουδών/ Level: Μεταπτυχιακό/ Postgraduate

The broad availability of data in every aspect of life has created an unprecedented interest in methods for extracting useful information and knowledge from data, which is the realm of Data Science. Data Science is a very hot and very active subject in the curricula of both graduate and undergraduate studies in Universities and Colleges throughout the world these days. Even though it is not a genuinely new domain of study per se, just recently acquired a new potential to rejuvenate and homogenize some more traditional domains of study with roots in intelligence, cognition and learning like Data Mining, Machine Learning, Knowledge Discovery in Databases, Pattern Recognition etc. In this course we will delve into the foundations and principles that underlie the techniques for extracting useful knowledge from data and we will illustrate each of these concepts with one or more data mining techniques that embodies these principles. One of the primary goals of this module is to help the students view real life problems from a data perspective and learn to apply a data analytic way in solving these problems systematically. This data analytic thinking will enable prospective data science professionals to develop intuition as to how and where to apply creativity and domain knowledge to the analysis of relevant problems. Hands on knowledge and experience will be acquired in this course through the exposure to various programming assignments and projects.

  • Κωδικός / Course Code: COS623
  • ECTS: 10
  • Τρόποι Αξιολόγησης / Assessment:

    -

  • Διάρκεια Φοίτησης/ Length of Study: Εξαμηνιαία (εαρινό)/ Semi-annual (spring)
  • Κόστος/ Tuition Fees: 450 euro
  • Επίπεδο Σπουδών/ Level: Μεταπτυχιακό/ Postgraduate
This course covers the methodology of designing cognitive systems through a historical overview of the field, the review of cognitive architectures, and the hands-on experimentation with cognitive architecture platforms. It considers the environment within which the system will operate, and discusses how to represent the salient features of that environment. It continues to investigate how the cognitive system interacts with the environment, specifying the characteristics of the sensors and actuators of the system. It investigates how to represent information internally in the system, and how to analyze the characteristics that this representation should have in terms of accessibility, scalability, persistence of the information. It then examines the processes internal to cognitive system that operate on the information, and analyzes the processes of learning and reasoning in terms of their desired behaviors, the guarantees they should offer, and their interaction. It concludes by considering ways to evaluate the performance of a cognitive system, and the process of error analysis for debugging and improving its performance.
  • Κωδικός / Course Code: COS622
  • ECTS: 10
  • Τρόποι Αξιολόγησης / Assessment:

    -

  • Διάρκεια Φοίτησης/ Length of Study: Εξαμηνιαία (χειμερινό) / Semi-annual (fall)
  • Κόστος/ Tuition Fees: 450 euro
  • Επίπεδο Σπουδών/ Level: Μεταπτυχιακό/ Postgraduate
The course examines the neural processes that underlie cognitive functions, such as attention, perception, and memory. It introduces basic neuroanatomy and modern methods and techniques (e.g., functional imaging, electrophysiology) that are used by scientists to draw inferences about cognition in the normal and abnormal brain.
  • Κωδικός / Course Code: COS621
  • ECTS: 10
  • Τρόποι Αξιολόγησης / Assessment:

    -

  • Διάρκεια Φοίτησης/ Length of Study: Εξαμηνιαία (εαρινό)/ Semi-annual (spring)
  • Κόστος/ Tuition Fees: 450 euro
  • Επίπεδο Σπουδών/ Level: Μεταπτυχιακό/ Postgraduate
This course will provide students with theoretical knowledge and practical skills for designing computerized experiments for behavioral research. The course will start by providing an in-depth analysis of experimental methodology and design. It will then proceed to provide students, by means of assignments, with hands-on experience in designing experiments, collecting data from human participants, analyzing and reporting the data, and interpreting statistical results. Through this course students are expected to acquire all the necessary knowledge on how to investigate scientifically research questions of interest.
  • Κωδικός / Course Code: COS614
  • ECTS: 10
  • Τρόποι Αξιολόγησης / Assessment:

    -

  • Διάρκεια Φοίτησης/ Length of Study: Εξαμηνιαία (εαρινό)/ Semi-annual (spring)
  • Κόστος/ Tuition Fees: 450 euro
  • Επίπεδο Σπουδών/ Level: Μεταπτυχιακό/ Postgraduate
This interdisciplinary course aims to underline the importance of incorporating human factors in the design and development of adaptive interaction systems. Incorporating cognitive and emotional human factors into adaptive applications and processes enhances the user experience, usability and satisfaction while users interacting with hypermedia environments. Main thematic areas emphasize upon the convergence of psychological theories and contemporary research on computer-mediated information processing. It will initially cover topics in the field of cognitive psychology, to the extent that there is an analogy with hypermedia information; on psychological issues with regards to the role of cognitive processing and emotions on information assimilation and learning performance capabilities; on emotional intelligence within the context of Web-based interaction, etc. At a second level, topics on personalization; adaptivity; user modelling; multi-modal interactions; task and user analysis; (adaptive) user interface design principles; user interface evaluation and usability testing; will be covered, to support the adaptation issue in various application levels.
  • Κωδικός / Course Code: COS613
  • ECTS: 10
  • Τρόποι Αξιολόγησης / Assessment:

    -

  • Διάρκεια Φοίτησης/ Length of Study: Εξαμηνιαία (χειμερινό) / Semi-annual (fall)
  • Κόστος/ Tuition Fees: 450 euro
  • Επίπεδο Σπουδών/ Level: Μεταπτυχιακό/ Postgraduate
This course studies the development of cognitive agents with computational models of argumentation as the underlying foundation for cognitive human reasoning. It brings together elements from argumentation theory in AI with cognitive psychology of reasoning to study a new form of symbolic representation and reasoning that reflects cognitive reasoning processes in humans, which leads to a new style of cognitive programming for cognitive systems. Specific elements that are covered include: The logical nature of human reasoning — argumentative decision making. Argumentation theory and Argumentation Logic in CS. Conditional human logic and argumentation logic. Cognitive reasoning about actions and change. Cognitive Knowledge Representation of common sense world knowledge and Cognitive Programming. Explanation, justification and persuasion through human-system argumentative dialogues. Argumentation-based agent architectures for adaptive agents. Application of cognitive agents to personalized and adaptive recommender systems and to elements of story comprehension.
  • Κωδικός / Course Code: COS524
  • ECTS: 10
  • Τρόποι Αξιολόγησης / Assessment:

    -

  • Διάρκεια Φοίτησης/ Length of Study: Εξαμηνιαία (εαρινό)/ Semi-annual (spring)
  • Κόστος/ Tuition Fees: 450 euro
  • Επίπεδο Σπουδών/ Level: Μεταπτυχιακό/ Postgraduate
The course presents basic notions from natural language processing, and uses existing tools to demonstrate how structured information can be extracted from natural language text, and how learning and reasoning can be applied on it. The course will present linguistic and statistical approaches for the different aspects of syntax, semantics and pragmatics of natural language. Algorithms and modern systems that address computational these issues will be studied. The distributional semantics approach to computational linguistics and its relevance to cognition will be presented. The link of natural language processing to the cognitive process of narrative text comprehension will be examined.

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