| Study programme competencies |
| Code | Study programme competences |
| A2 | CE2 – To define, evaluate and select the architecture and the most suitable software for solving a problem in the field of bioinformatics |
| A3 | CE3 – To analyze, design, develop, implement, verify and document efficient software solutions based on an adequate knowledge of the theories, models and techniques in the field of Bioinformatics |
| A4 | CE4 - Ability to acquire, obtain, formalize and represent human knowledge in a computable form for the resolution of problems through a computer system in any field of application, particularly those related to aspects of computing, perception and action in bioinformatics applications |
| B1 | CB6 - Own and understand knowledge that can provide a base or opportunity to be original in the development and/or application of ideas, often in a context of research |
| B2 | CB7 - Students should know how to apply the acquired knowledge and ability to problem solving in new environments or little known within broad (or multidisciplinary) contexts related to their field of study |
| B6 | CG1 -Search for and select the useful information needed to solve complex problems, driving fluently bibliographical sources for the field |
| B7 | CG2 - Maintain and extend well-founded theoretical approaches to enable the introduction and exploitation of new and advanced technologies |
| C1 | CT1 - Express oneself correctly, both orally writing, in the official languages of the autonomous community |
| C6 | CT6 - To assess critically the knowledge, technology and information available to solve the problems they face to. |
| Learning aims | |||
| Learning outcomes | Study programme competences | ||
| Knowledge and application of the fundamental principles and techniques of AI and their practical application | AJ2 AJ3 AJ4 |
BJ1 BJ2 BJ6 BJ7 |
CJ1 CJ6 |
| Contents |
| Topic | Sub-topic |
| 1. Introduction | 1.1. An historical perspective 1.2. Preliminary aspects 1.3. General considerations |
| 2. Problem-solving | 2.1. Introduction to solving problems in AI 2.2. The state space concept. Searching 2.3. General characteristics of searching processes 2.4. Pure search strategies 2.5. Search strategies in state space |
| 3. Structured Knowledge Representation | 3.1. Introduction 3.2. Declarative methods 3.3. Procedural methods 3.4. Examples and a practical case 3.5. Production systems |
| 4. Reasoning in AI | 4.1 Basics of categorical reasoning 4.2 Basics of Bayesian reasoning |
| 5. Development of Intelligent Systems | 5.1 Introduction to Knowledge Engineering 5.2 Methodologies for knowledge modeling 5.3 CommonKADS 5.4 Case study |
| Planning | ||||
| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Laboratory practice | B2 B6 B7 C1 C6 | 28 | 56 | 84 |
| Guest lecture / keynote speech | A2 A3 A4 B1 | 14 | 28 | 42 |
| Personalized attention | 0 | 0 | ||
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | ||||
| Methodologies |
| Methodologies | Description |
| Laboratory practice | Use of symbolic AI techniques to solve problems. |
| Guest lecture / keynote speech | Teaching the contents of the course, promoting involvement of students. |
| Personalized attention |
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| Assessment | |||
| Methodologies | Competencies | Description | Qualification |
| Guest lecture / keynote speech | A2 A3 A4 B1 | Written test to evaluate the knowledge about the course |
60 |
| Laboratory practice | B2 B6 B7 C1 C6 | Submission before the deadline and attendance will be evaluated |
40 |
| Assessment comments | |||
| Sources of information |
| Basic | |
 Moret et al. (2005). Fundamentos de inteligencia artificial. Servicio de publicaciones de la UDC (2ª ed, 2ª imp) José T. Palma, Roque Marín Morales et al. (2008). Inteligencia artificial - Técnicas, métodos y aplicaciones. McGraw Hill (1ª ed.) Russell & Norvig (2004). Inteligencia artificial: un enfoque moderno. Pearson (2ª ed) |
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| Complementary | |
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| Recommendations | |||
| Subjects that it is recommended to have taken before | |
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| Subjects that are recommended to be taken simultaneously |
| Subjects that continue the syllabus | |||
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| Other comments | |