6 ECTS credits
150 h study time

Offer 3 with catalog number 1023838BNR for all students in the 1st and 2nd semester at a (B) Bachelor - advanced level.

Semester
1st and 2nd 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
Educational team
Geraint Wiggins (course titular)
Activities and contact hours
28 contact hours Lecture
26 contact hours Seminar, Exercises or Practicals
Course Content

This course presents a broad and deep coverage of the fundamental concepts of a range of approaches to Artificial Intelligence.

1.    Introduction to Artificial Intelligence
2.    Intelligent Agents
3.    Knowledge Representation and Reasoning
4.    Searching for Solutions
5.    Learning to classify
6.    Representing and reasoning with uncertainty

Additional info

Latest information about the course is provided in the relevant Canvas site. The course follows chapters 1-10, 13-14 and 26-27 of Artificial Intelligence: A Modern Approach, Prentice Hall, by Stuart Russell and Peter Norvig, latest edition, though older editions are adequate. Slides used during lecture presentations will be available on Canvas.
On the course book webpage, http://aima.cs.berkeley.edu/, other related information can be found, such as "Al Resources on the Web", and an "Online Code repository.

 

Learning Outcomes

General competencies

•    Knowledge and insight: On passing this course, a student will have a good overview and basic knowledge of symbolic AI-techniques, formalisms and their applications.
•    Application of knowledge and insight: On passing this course, a student will be able to make judgements about when particular techniques should be applied to solve particular problems and to compare and contrast the advantages of different techniques for particular problems.
•    Independent thinking: On passing this course, a student will be equipped to collect and interpret literature about topics in AI. He or she will be able to understand basic and intermediate literature to a sufficient level to implement AI solutions to given problems.
•    Communication: On passing this course, a student will be able to communicate ideas about symbolic AI to experts and non-experts.
•    Skills: On passing this course, a student will have further developed independent learning skills and autonomy in scientific and engineering work.

 

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

Written Examination.

Students BA AI have to write an essay with peer 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:
Bachelor of Computer Science: Default track (only offered in Dutch)
Bachelor of Mathematics and Data Science: Standaard traject (only offered in Dutch)
Bachelor of Artificial Intelligence: Default track (only offered in Dutch)