Sisältöhaku

455522S:2

In this two day course we will examine various machine learning (and statistical learning) methods and their relationship to persuasive systems design. When designing personalized persuasive systems, often the personalization is based on user data, hence, a proper understanding of modern data science methods is key for successful personalized persuasive systems design. This course will cover supervised learning and reinforcement learning (multi-armed bandit problems), and it will explore rece...

816616J

After completing the course the student will be able to:* understand and discuss the impact of the ICT in the society and changes that take place,* understand how information systems transform ways of communication and interaction,* form an overview of how human and societal traits and ICT co-exist, for example, through a series of paradoxes as well as* gain basic understanding of behaviour change, behaviour analysis and digital intervention design as regards technology. See information and d...

817619S:1

The major objectives of this course is - to get anxiety and fear out of statistical analysis - to acquire basic skills in quantitative study - to know how to use SPSS Contents for the course: - design a quantitative study in forms of questionnaire - prepare a codebook - prepare a data file with SPSS - do preliminary analyses with SPSS, including descriptive statistics, data manipulation, check reliability of a scale and statistical methods selection

407040A:8

Upon completion of the course the students will be able to: - Deeply understand the fundamentals common to widely used in robotics and autonomous systems. - Design and analyze planning algorithms. - Apply the material to critical problems in robotics, internet of things, and virtual and augmented reality. - Understand the links between theory and practice in sensing, filtering. and autonomous systems.

521257S:1

Kevään 2022 toteutus Laajuus: 5 op / 133 tuntia opiskelijan työtä Opetuskieli: suomi Ajoitus: Opintojakso järjestetään kevätlukukaudella, periodilla 4. Suositeltava suoritusajankohta opintojaksolle on kandiopintojen 1. vuosi. Osaamistavoitteet: Kurssin suoritettuaan opiskelija osaa * kuvailla mallintamisen yleiset periaatteet, * kuvailla mallintamisen merkityksen tietojärjestelmien suunnittelussa, * käyttää erilaisia mallintamismenetelmiä kuvaamaan ja suunnittelemaan tietojärjestelmiä eri näk...

812360A:2

Upon completion of the course, the student will be able to: - design and execute a small-scale data mining project - design a research plan and formulate research questions - select pre-processing methods appropriate for a given data setselect appropriate data mining and data analysis methods based on the data and the research questions - apply the selected methods to a real-world data set - interpret and evaluate the results of the analysis - present the results of the project and report the...

521251S:1

812355A:3

ID00BQ11-3014_TVT19SPL

You can use the course code 'mobile2' to enrol. --- This course focuses on one of the core demands of the industry today: an understanding of mobile user interaction, computing constraints, an introduction to mobile development (Android) covering multiple aspects of the platform. This is a 5 ECTS course, with both lectures and practical sessions (labs). After this class, students can: - design and prototype a mobile user interface taking into account usability aspects of interaction on smalle...

521046A:3