
- Opettaja
Alexandra Virtanen
The seminar is intended to be a roundtable for computer science (CS)
graduate students and researchers. It is based on contemporary academic
and professional materials in and related to CS.
The course introduces methods and algorithms for extracting information and knowledge from data sets. This includes techniques for data pre-processing, visualizing high-dimensional data, basic machine learning methods for supervised learning (classification, regression), unsupervised learning (clustering, association rule analysis), model selection and validating how well a learned model predicts on new data (holdout, cross-validation). The CRISP-DM process model is introduced as a tool for analysing and implementing data science projects.
Prerequisites: Python programming skills. Basic knowledge of probability, statistics and linear algebra is beneficial. Taking the course TKO_7093 Statistical Data Analysis before this course is recommended.
Objectives
After completing the course, the student will be able to
- understand basic and advanced deep neural network architectures and their application to various challenges in natural language processing
- select appropriate language resources and deep learning models and fine-tune state-of-the-art models for a range of tasks involving natural language
- understand and explain the capabilities and limitations of deep learning-based models and concepts such as transfer learning, multi- and cross-lingual models, and large-scale pre-training
- independently implement multi-stage natural language processing systems combining several task-specific models
· Opiskelija tietää mitä design ajattelu on
· Opiskelija ymmärtää design ajattelun perusteita ja niiden käyttöä terveyden- ja sosiaalihuollossa
· Opiskelija soveltaa design ajattelun prosessia ja menetelmiä terveyden- ja sosiaalihuollon haasteiden ratkomisessa
· Opiskelija kykenee arvioimaan design ajattelun käytettävyyttä myös muissa opinnoissa ja työelämässä
· Opiskelija saa tietoa yrityksen perustamisesta ja idean kaupallistamisesta
The course is designed to give a wide perspective of terms and practices
in digital art and visual communication though interactive mediums. It
will present multidisciplinary and cross-media framework of the study
engaged by various cases from IT and game development practices.
The historical framework of art practices will be addresses widely,
following the principles of conventional art theory and analysis for
pursuing developing practices in contemporary mediums of expression and
storytelling, such as interactive digital mediums and video games. The
agenda of the course is planned to provide an extensive insight into the
present practices of digital art creation (2D and 3D, UI/UX design and
animation).
Tavallisissa populaatiomalleissa oletetaan, että lajin asuinalue on suuri yhtenäinen alue, jossa elinolosuhteet ovat kaikille yksilöille samanlaiset. Metapopulaatio taas koostuu useista paikallisista populaatioista, joiden välillä on muuttoliikettä. Kurssilla käsitellään dynaamista peliteoriaa erilaisissa metapopulaatiomalleissa, sovelluksena muun muassa muuttoliikkeen evoluutio.
Kurssiavain: peliteoria
The course takes a practical look at game testing at different development stages (i.e. production testing, quality assurance and play testing) and presents issues typical to particular game genres.
By the end of the course the student
is familiar with with different phases and types of game testing
can create and oversee a usability test plan for a game
can create and oversee a user experience test plan for a game
has experience in bug hunting and ascertaining their seriousness
is confident in reporting to and collaborating with game developers
knows how to test different types of games such as serious games
The course concentrates on the basics of gamification and serious games
using a practical approach. The aim is that the students understand and
master the skills to make experiences more fun and engaging.
Genetiikan LuK vaiheen opintoja, soveltuu myös sivuaineopiskelijoille
The course covers the practices of green programming and related concepts. It explores how to measure and optimize system energy consumption as part of software development. The goal is for the student to be able to identify key factors of energy consumption in a web application, apply their learning as part of a software development project, and design software systems to be energy-efficient after completing the course.