Introduction Artificial Intelligence A
Course infoSchedule
Course moduleSOW-BKI135
Credits (ECTS)3
CategoryB1 (First year bachelor)
Language of instructionEnglish
Offered byRadboud University; Faculty of Social Sciences; Artificial Intelligence;
L.W. Ansteeg, MSc
Other course modules lecturer
Contactperson for the course
L.W. Ansteeg, MSc
Other course modules lecturer
prof. dr. M.A.J. van Gerven
Other course modules lecturer
prof. dr. T.M. Heskes
Other course modules lecturer
Academic year2020
PER1  (01/09/2020 to 01/11/2020)
Starting block
Course mode
Registration using OSIRISNo
Course open to students from other facultiesYes
Waiting listNo
Placement procedure-

The overall learning aims of the course are that students will be able to:

  • Recognise typical AI problems, explain typical features of AI problems and think up examples of AI problems.
  • Explain the relationship between a problem space and a search tree, explain fundamental search methods and their differences, produce an algorithm in pseudo code for elementary search techniques and select and apply search techniques in basic examples.
  • Explain the essence of different AI methods and elaborate on the details of these methods in basic examples.

The aim of the course is to give students a first impression of the field of Artificial Intelligence, without going into too much technical detail. The course will cover:

  • What Artificial Intelligence is and an example of how AI techniques can be applied to an existing software system.
  • Fundamental search techniques and their application.
  • Types of knowledge representation, the main languages which are used and an example of their application in the field of Artificial Intelligence.
  • Learning through computers, the main techniques which are used and an example of their application.
  • Implications of AI
Presumed foreknowledge
Some knowledge of mathematics, programming and formal logic is beneficial.
Test information
Multiple-choice exam: 90%, minimum passing grade 5.5.
Assignments (honest effort): 10%, minimum passing grade 5.5: no resit possible.
Please sign up for any course at (, it is obligatory.

Students who are enrolled for a course are also provisionally registered for the exam. Pay attention: participation in the exam is only possible if all relevant conditions laid down nin the EER are met. Students who, after being checked are found not to meet these conditions, shall be excluded from the exam. In that case participation is possible on special grounds and with a permit written by the student counselor. 

Re-examination: register at ( until five days prior to the date of the exam.

We urge you to always read the course information on Brightspace. There are courses for which you are obliged to register for tutorials and/or practicals
Required materials
Poole, D.I.R. & Mackworth, A.K.P. Artificial Intelligence: Foundations of Computational Agents (2nd ed.). Cambridge University Press, 2017. (The entire book is legitimately available via

Instructional modes

Practice sessions

Question-and-answer seminars

Test weight90
Test typeDigital exam with CIRRUS
OpportunitiesBlock PER1, Block PER2, Block PER4

Test weight10
Test typeAssignment
OpportunitiesBlock PER1