Checking date: 23/05/2022


Course: 2022/2023

Artificial Intelligence
(17306)
Study: Bachelor in Data Science and Engineering (350)


Coordinating teacher: FERNANDEZ REBOLLO, FERNANDO

Department assigned to the subject: Department of Computer Science and Engineering

Type: Electives
ECTS Credits: 6.0 ECTS

Course:
Semester:




Objectives
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.
Skills and learning outcomes
Description of contents: programme
· Introduction to artificial intelligence · Production systems · Search · Reasoning under uncertainty · Application areas
Learning activities and methodology
LEARNING ACTIVITIES AND METHDOLOGY THEORETICAL-PRACTICAL CLASSES. 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. Individualized attendance (individual tutoring) or in-group (group tutoring) for students with a teacher. STUDENT INDIVIDUAL WORK OR GROUP WORK WORKSHOPS AND LABORATORY SESSIONS FINAL EXAM. 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.
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40
Calendar of Continuous assessment
Basic Bibliography
  • S. Russell, P. Norvig. Artificial Intelligence: A modern approach. Prentice Hall.

The course syllabus may change due academic events or other reasons.