Language: English
Introduction to satellite positioning
Max amount of FITech students: 20 adult learners This course provides the introduction to satellite based positioning, with focus on the Global Navigation Satellite Systems (GNSS). Course contents Core content: Complementary knowledge Specialist knowledge Learning outcomes After completing the course, the student knows how to Course material Global Positioning System: Signals, Measurements, and Performance, Misra,
Usability, user experience and analytics
On the course, the student learns to evaluate the usability and user experience of products, to understand how they affect the success of products, and to design usable, enjoyable software products and services. Students practice usability assessment skills of services using e.g. Nielsen’s 10 heuristic rules. Common design tools are applied to user interface sketching
Information search and generation with large language models
Modern AI applications do not rely on language models alone as their source of knowledge. They often combine prompts, search systems, external data sources and evaluation methods to find, generate and use information. This course introduces large language models, AI-based information search, query and prompt design, and retrieval-augmented generation from both theoretical and practical information-use
Data-intensive programming
The course discusses various concepts of data engineering, such as big data, Apache Spark, data lakes, and technologies for storing and processing large datasets. Students gain hands-on experience in developing data processing pipelines in a cloud-based environment. Course contents Principles of big data and big data processing platforms The Apache Spark programming model Databricks data
Trends in cyber security
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. This course introduces key and current themes in cyber security from the perspective of the individual citizen and everyday life, rather than from an organisational or institutional standpoint. The
Health innovations – from ideas to impact in device development
Max amount of FITech students: 15 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. Course contents The course introduces students to the fundamentals of health device development and the innovation process. Students will become familiar with the design thinking approach and the importance
Acquisition and analysis of biosignals
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 The course covers the origin, acquisition, and analysis of biosignals such as ECG, EEG, EMG, and PPG. Students learn signal processing methods and develop practical skills in
Johdatus bioinformatiikkaan
Maksimimäärä FITech-opiskelijoita: 5 aikuisopiskelijaa Kurssin sisältö Kurssi johdattaa opiskelijat bioinformatiikan keskeisiin käsitteisiin ja menetelmiin. Kurssilla perehdytään DNA- ja proteiinitietokantoihin, sekvenssien vertailuun ja proteiinien 3D-rakenteiden tarkasteluun. Käytännön taitoja harjoitellaan verkkotyökaluilla ja harjoitustehtävillä Bioinformatiikan perusteet ja sovellusalueet DNA- ja proteiinisekvenssit ja niiden tietokannat Proteiinirakenteet, DNA-sekvensointi Sekvenssien vertailumenetelmät AlphaFold-tekoälymenetelmä Osaamistavoitteet Opintojakson suoritettuaan opiskelija osaa kuvata bioinformatiikassa käytettävän datan ja
Tekoälyn perusteet
Kurssin sisältö Peruskurssi koneoppimisen (tekoälyn) tärkeimmistä menetelmistä. Koneoppiminen tarjoaa tietotekniikan opiskelijoille uuden lähestymistavan ongelmanratkaisuun perinteisen ohjelmoinnin rinnalle. Tällä kurssilla opiskelija oppii ymmärtämään ja ohjelmoimaan koneoppimisen perusmenetelmiä. Lineaarinen regressio Lineaarinen luokittelu Todennäköisyyksiin perustuva päättely Neuroverkot Päätöspuut ja satunnaismetsät Ryvästys Monisto-oppiminen Vahvistusoppiminen Osaamistavoitteet Tekoälystä on tullut merkittävät osa tietotekniikkaa ja tietotekniikan sovelluksia kuten itseajavat autot, keskustelevat kielimallit
Deep learning
A course on deep learning covering athematical and statistical principles of deep learning and selecting suitable deep neural network layers and processing operations for specific tasks. Course contents Deep neural networks layers: convolutional neural networks, recurrent neural networks, transformers, multilayer perceptrons Components of deep neural networks: nonlinearities, normalization, subsampling Task-specific loss functions Training deep neural