Student Type: Tutkinto-opiskelija
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
Machine learning: Supervised methods
Max amount of FITech students: 40 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. Mastering the prerequisite skills is very important in order to complete this course. Please list your preliminary knowledge in your application. Course contents Generalisation error analysis and estimation Model
Computer vision
Max amount of FITech students: 50 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. The course gives an overview of algorithms, models and methods which are used in automatic analysis of visual data. Course contents Image formation and processing Feature detection and matching
Speech processing
Max amount of FITech students: 10 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. Course contents After the course, the student is able to describe and make use of basic phenomena in speech communication, and describe and apply common speech processing methods, especially