Study university: University of Oulu
Johdatus tietokonejärjestelmiin
Tällä kurssilla käsitellään tietokoneen arkkitehtuuria ja keskusyksikön (CPU) toimintaa. Kurssin aiheita ovat tietotyypit ja muistinhallinta, keskeytykset, laiterekisterit ja I/O, tietokoneen ohjelmointi ja laiteläheinen ohjelmointi sekä C-kielen perusteet. Kurssin suoritettuaan opiskelija ymmärtää tietokoneen arkkitehtuurin ja keskusyksikön toiminnan yleisellä tasolla. Lisätietoa kurssista Oulun yliopiston kurssisivulla. Tämän kurssin suorituksesta on mahdollista saada digitaalinen suoritusmerkki.
Introduction to artificial intelligence
Max amount of FITech students: 100 Persons without a valid study right to a Finnish university have preference to this course. The course considers basic methods and problem solving with artificial intelligence-based approaches. The course is concentrated around concepts of search, regression, classification and clustering. The course highlights differences between supervised and unsupervised learning. The
Digital image processing
Max amount of FITech students: 30 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. The course gives an introduction to digital image processing methods. The emphasis is in various image filtering techniques implemented both in spatial and frequency domains. Also, image compression and
Artificial intelligence
Max amount of FITech students: 30 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. This course presents the student overview of some of the basic AI theories and applications with practicality in mind. In the course projects, students get some experience in programming
Machine learning
Max amount of FITech students: 30 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. Machine learning principles are described in lectures and practical hands-on programming tasks are done on the online Matlab platform. Course contents Learning outcomes After completing the course, student Course
Deep learning
Max amount of FITech students: 30 Please note the early application deadline. This course provides an elementary hands-on introduction to deep learning. Students taking this course will learn the theories, models, algorithms, implementation and recent progress of deep learning and obtain empirical experience on training deep neural networks. Applications of deep learning to typical computer
Towards data mining
Max amount of FITech students: 200 Persons without a valid study right to a Finnish university have preference to this course. In this course, you will learn the fundamental skills for data collection and preprocessing, enabling you to succeed in your data mining tasks. Course contents Amount and quality of data plays a major role