Programming (Course: 1 / Semester: 1) Discrete Mathematics: (Course: 1 / Semester: 2)

In this course the fundamentals of Artificial Intelligence techniques will be seen from the conceptual point of view and from the practical point of view.

K5: Knowledge and application of the basic algorithmic procedures of computer technologies to design solutions to problems, analyzing the suitability and complexity of the proposed algorithms. K12: Knowledge and application of the fundamental principles and basic techniques of intelligent systems and their practical application. S2: Ability to understand the fundamentals, paradigms and techniques of intelligent systems and to analyze, design and build systems, services and computer applications that use these techniques in any field of application. S7: Ability to understand and master the basic concepts of discrete mathematics, logic, algorithms and computer programs with application in engineering. C7: Ability to understand and implement intelligent systems paradigms and techniques in the analysis, design and development of advanced computing solutions, applicable to various areas such as automation, machine learning and decision making. C8: Ability to identify, understand and solve mathematical problems in the field of computer engineering, related to the development of technological solutions and the generation of efficient and optimized software.

1. An Introduction of AI 2. Production Systems 3. Search a. Introduction b. Uninformed Search c. Heuristic Search 4. Uncertainty a. Probability calculus b. Bayesian calculus. Bayes theorem. Bayesian inference. Bayesian Networks c. Markov based models. Markov chains. Markov models. Hidden Markov Models. Markov Decision Processes (MDP). Partially observable MDPs (POMDP). d. Fuzzy logic 5. Robotics 6. Applied Artificial Intelligence

LEARNING ACTIVITIES AND METHDOLOGY THEORETICAL-PRACTICAL CLASSES. [44 hours with 100% classroom instruction, 1.67 ECTS] Knowledge and concepts students must acquire. Student receive course notes and will have basic reference texts to facilitate following the classes and carrying out follow up work. Students partake in exercises to resolve practical problems and participate in workshops and evaluation tests, all geared towards acquiring the necessary capabilities. TUTORING SESSIONS. [4 hours of tutoring with 100% on-site attendance, 0.15 ECTS] Individualized attendance (individual tutoring) or in-group (group tutoring) for students with a teacher. STUDENT INDIVIDUAL WORK OR GROUP WORK [98 hours with 0 % on-site, 3.72 ECTS] WORKSHOPS AND LABORATORY SESSIONS [8 hours with 100% on site, 0.3 ECTS] FINAL EXAM. [4 hours with 100% on site, 0.15 ECTS] Global assessment of knowledge, skills and capacities acquired throughout the course. METHODOLOGIES THEORY CLASS. Classroom presentations by the teacher with IT and audiovisual support in which the subject's main concepts are developed, while providing material and bibliography to complement student learning. PRACTICAL CLASS. Resolution of practical cases and problem, posed by the teacher, and carried out individually or in a group. TUTORING SESSIONS. Individualized attendance (individual tutoring sessions) or in-group (group tutoring sessions) for students with a teacher as tutor. LABORATORY PRACTICAL SESSIONS. Applied/experimental learning/teaching in workshops and laboratories under the tutor's supervision.