4 ECTS credits
100 h study time

Offer 1 with catalog number 8024157GNR for all students in the 1st semester at a (G) Postgraduate - preliminary level.

Semester
1st semester
Enrollment based on exam contract
Impossible
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Yes
Taught in
English
Faculty
Faculty of Sciences and Bioengineering Sciences
Department
Computer Science
Educational team
Leticia Arco García
Johan Loeckx (course titular)
Activities and contact hours
30 contact hours Lecture
8 contact hours Seminar, Exercises or Practicals
Course Content

This module gives a basic introduction to the concepts and principles of AI. It explains what AI is, why it is an important evolution, how it works conceptually, what the limits are, and potential. It is mainly aimed to remove common misconceptions, create a common ground and language between the participants and empower them with a framework of understanding for future learnings. 

 
Additional info

 

 
 
Learning Outcomes

General Competences

  1. The student has a basic understanding of the domain of AI is and can give examples within a concrete context of what makes a solution “intelligent”.  
  2. The student can explain the meaning and identify the three layers of AI (“definition”, “formalisation” and “implementation”) for a given application. 
  3. The student understands the main approaches to AI and can illustrate them with concrete examples.  
  4. The student understands why AI is an important (r)evolution, how it is different from regular IT, how it came about, what the dangers are with respect to quality, fairness, discrimination, ethics, and democracy and how it can bring a positive impact. 
  5. The student understands the (generic) functionality that AI can provide and can give examples how AI can augment and improve existing products or solutions. 
  6. The student appreciates the roots of AI and can show through concrete examples and applications, how the underlying philosophical assumptions have a crucial impact on the capabilities and limitations of AI. 
  7. The student can describe the limits of AI algorithms & computational representations. 
 

Grading

The final grade is composed based on the following categories:
Written Exam determines 100% of the final mark.

Within the Written Exam category, the following assignments need to be completed:

  • Written Exam with a relative weight of 1 which comprises 100% of the final mark.

Additional info regarding evaluation

 

 
 
Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Postgraduate Certificate AI for the Common Good: Default track