Curricula Guides
2018–2019
Archived Curricula Guide 2017–2019
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
Recommended:
TIETA6
Data Structures
Corresponding course units in the curriculum
Learning outcomes
After taking this course the student knows the basic methods of neurocomputing and their applications in different problems.
Contents
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
EnglishModes 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.
Evaluation
Numeric 1-5.Study materials
Haykin S., Neural Networks: A Comprehensive Foundation, 2. edition, Prentice Hall, 1999.
Belongs to following study modules
Faculty of Natural Sciences
Faculty of Natural Sciences
Faculty of Natural Sciences
Faculty of Natural Sciences
Faculty of Natural Sciences
2018–2019
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Faculty of Natural Sciences