Student Type: Adult learner
Machine learning
Max amount of FITech students: 60 adult learners The main concepts as well as the different types of machine learning are covered on this course. The approach of this course is to cover machine learning from algorithmic point of view. The aim of this approach is to understand the theories/algorithms behind machine learning algorithms 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
Speech recognition
Max amount of FITech students: 20 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. Course contents After completing the course you will have become familiar with speech recognition methods and applications. Additionally, you will have learned to understand the structure of a typical
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 Learning outcomes After the course, the
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 Learning outcomes After the course, the student Course
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
Bayesian data analysis
Max amount of FITech students: 100 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. Course contents Learning outcomes After the course, the student can Teaching schedule It is possible to
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