Duration
30h Th
Number of credits
| Master in psychology (120 ECTS) | 3 crédits |
Lecturer
Coordinator
Language(s) of instruction
French language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The course is an introduction to artificial intelligence (AI) for psychologists. The main topics are: AI history, networks (semantic, slipnet), modeling of intellectual fluidity, theoretical framework of neural networks, the challenges facing connectionist approaches and their correspondents in the organization of the mind, deep networks, representation of forms and their matching, artificial life (genetic algorithms). The different concepts will be presented with examples and matlab applications.
More details (powerpoint presentations, course videos, matlab programs and various notes) can be found in the 2019-2020 course website
Why an introduction to AI for psychologists?
- AI has become a societal phenomenon and is a source of for psychologists. The discipline is becoming increasingly important in the intellectual and economic life, it impacts or will impact more and more professional life, training and tutorials.
- AI, just like mathematics and computer science, provides a toolkit for generating and testing models; it is likely to be in the future for psychologists as useful as statistics are today.
- Some familiarity with AI and programming is an definite advantage in the job market whether for the development of intelligent systems, or for their training and assessment of their human-like behavior.
- With AI, a new kind of thought is emerging. The psychologist who is, among others, a specialist in scientific approaches to mental phenomena cannot ignore it.
Learning outcomes of the learning unit
The course must provide to the student a series of basic concepts used in the study of cognitive phenomena and give her useful elements for the formalization of a number of intellectual processes.
Prerequisite knowledge and skills
Basic mathematical concepts (graph, function, basic operations on matrix) - General cognitive Psychology
Planned learning activities and teaching methods
The course takes different forms: lectures, programming exercises with matlab.
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face, using smartboard. Video versions of the courses (audio and presentation screens) will also be available.
Organisational adjustments related to the current health context
In case of "code jaune", nothing will be changed to the way the assessments will be organized.
In case of "code orange", the assessments will be done remotely with LifeSize. The exam will allow students to prepare written answers to the questions asked during the interview and then to present them orally.
Recommended or required readings
Copies of slides, notes on specific topics and an optional reading list are provided.
Assessment methods and criteria
Below you will find information on the evaluation methods planned for in-person and remote exams as well as those planned for hybrid sessions. Depending on how the health crisis evolves, the chosen method will be communicated to you no later than one month before the start of the exam session.
Any session :
- In-person
oral exam
- Remote
oral exam
- If evaluation in "hybrid"
preferred in-person
Additional information:
Participation in computer labs, presentation of a personal work and oral exam with prior written preparation on the subjects covered in the course. Students will be judged on their ability to identify appropriate quantitative approaches to the study of the mind, to perceive their limits and to apply accurately and rigorously the methods presented in the course.
Work placement(s)
Organizational remarks
Contacts
D.Defays (ddefays@uliege.be)
J.Sougné (jsougne@ulg.ac.be)