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Archived Curricula Guide 2015–2017
Curricula Guide is archieved. Please refer to current Curricula Guides
TIETS07 Neurocomputing 5 ECTS
Organised by
Degree Programme in Computer Sciences
Person in charge
Professor Martti Juhola
Preceding studies
Data Structures, basics of mathematics.
Corresponding course units in the curriculum
School of Information Sciences
Curricula 2012 – 2015
TIETS07 Neurocomputing 5 ECTS

Learning outcomes

After taking this course the student knows the basic methods of neurocomputing and their applications in different problems.


Methods of neurocomputing and algorithms in conjunction with networks with forward and backward input are examined. Topics include also the supervised and unsupervised learning of neural networks. The examined methods are discussed in the context of application examples such as making various inferences.

Teaching methods

Teaching method Contact Online
Lectures 24 h 0 h
Exercises 10 h 0 h

Teaching language


Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Open University Students
  • Doctoral Students
  • Exchange Students
Lectures, exercises and exam.  Participation in course work 
In English

Written examination and active participation in exercises.


Numeric 1-5.

Study materials

Haykin S., Neural Networks: A Comprehensive Foundation, 2. edition, Prentice Hall, 1999.

Belongs to following study modules

School of Information Sciences
School of Information Sciences
School of Information Sciences
Archived Teaching Schedule. Please refer to current Teaching Shedule.
School of Information Sciences