SOW-BKI316
Mathematics 2 for Artificial Intelligence
Course infoSchedule
Course moduleSOW-BKI316
Credits (ECTS)6
Category-
Language of instructionEnglish
Offered byRadboud University; Faculty of Social Sciences; Artificial Intelligence;
Lecturer(s)
Contactperson for the course
L.E.C. Jacques
Other course modules lecturer
Coordinator
dr. S.A. Terwijn
Other course modules lecturer
Examiner
dr. S.A. Terwijn
Other course modules lecturer
Academic year2018
Period
SEM1  (03/09/2018 to 03/02/2019)
Starting block
SEM1
Course mode
full-time
Remarks-
Registration using OSIRISYes
Course open to students from other facultiesNo
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims
Upon completion of the course, students will be familiar with the use of complex numbers and techniques from probability theory, as well as with applications of these in information theory, data compression, and signal analysis. 
Content

During the Mathematics 2 course students will learn about:

  • The concepts of entropy, information and uncertainty
  • Markov chains and how they can be used to analyse certain processes
  • Signals
  • The properties of periodic signals
  • Using complex numbers
  • How signals can be seen in the time and frequency domain
  • A number of signal analysis methods, especially Fourier analysis
  • How filters can be used to locate signals between noise and artefacts
Levels
AI-B2

Test information
There will be one written exam at the end of the course. During the course there will be homework assignments that will count for 20% of the final grade.

Prerequisites
Mathematics 1 for AI (SOW-BKI104) or any course with comparable content and Linear Algebra (SOW-BKI124).

Contact information
Dr. S.A. Terwijn; E: s.terwijn@math.ru.nl; T: 024-365 2073

Required materials
Learning Management System (Brigthspace)
Don, Henk and Slagter, Luud. Lecture Notes, Available via Brightspace.

Instructional modes
Homework assignments

Lecture

Tutorials

General
Students will be supervised while they work on their homework.

Tests
Exam
Test weight1
Test typeExam
OpportunitiesBlock SEM1, Block SEM2