Student Type: Aikuisopiskelija
Social media analytics
Max amount of FITech students: 100 This course introduces social media as a data source and platform for understanding, exploring, and solving various societal issues. The relevant theoretical concepts around social media, analytic tools, and affordances of different social media platforms such as Twitter, Facebook, Instagram and YouTube will be discussed in detail. The students
Digital platform economy
Course content overlaps with course CS-E5310 ICT enabled service business and innovation (5 ECTS). Please choose only one of them. Course content Enablers of digitalisation, convergence, commoditisation, consumerisation (of IT), democratisation, disaggregation, disintermediation, power of digital aggregators and intermediators, specialisation, lowering entry barriers, servitisation, datafication, mobility, social media. Platforms, platform economy, network effects, boundary resources
Ohjelmoinnin perusteet
Tämä kurssi tarjoaa yliopisto-opiskelijoille perustiedot ohjelmoinnista sekä teorian että käytännön näkökulmasta. LUTin ensimmäinen ohjelmointikieli on ollut jo vuosia Python, sillä se sopii hyvin mm. ohjelmoinnin opiskeluun ja datan analysointiin. Tämän kurssin tavoitteena on ymmärtää ohjelmoinnin taustat ja historia sekä luoda vahva pohja muiden ohjelmointikielten opiskeluun Pythonin lisäksi. Kurssilla ei ole esitietovaatimuksia ja kaikki kurssin suorittamiseen
Advanced course on databases
The course presents advanced topics in databases, like physical storage and indexing, query processing and optimisation, transaction processing, concurrency control and error recovery. After completing the course, the student will be able to: Student can choose to study the course online or attend the lectures. The exam is organised in Turku or Vaasa. More information
Analytics for industrial internet
Course objectives: Understand and apply digital sampling Applying up-sampling and down-sampling Understand and apply digital filtering techniques (FIR, IIR) Applying different signal refinement and analytics algorithms, such as signal averaging, Independent Component Analysis (ICA) and Principal Component Analysis (PCA) Understand and apply sparse signal handling such as sparse sampling Understand and apply Kahlman filters Apply
Acquisition and analysis of biosignals
Course content Review of different physiological signals such as heart rate, body and skin temperature, blood pressure, oxygen saturation and respiration rate etc. which can be monitored by wearables. What kind of sensor technology is required to capture each of these physiological signals. Signal conditioning and processing for different types of biosignals; for example electrocardiography
Autonomic software and systems
NB! You can find this course on the application form under the study programme Åbo Akademi FITech-ICT courses 4/2021 and choosing the right course from the dropdown menu. Åbo Akademi will send you more information on the course practicalities ca 2 days after the application period has ended. Different degrees of autonomy are pervasive in
Software safety
The course explores the fundamental of safety systems engineering and the connection to advance methodologies to design complex technological systems. It focuses on teaching new approaches, frameworks, and theories to analyze, design, deploy and manage engineering systems with focus on safety. You will be introduced to new techniques for assisting the determination of requirements in
Energy technology
This minor will be offered through FITech for the last time in the academic year 2021-2022. Please also note that the application deadline for courses belonging to a minor that are offered in the spring semester is exceptionally already on November 1st. Please check the individual courses for updates regarding future availability. University of Vaasa
Machine learning with Python
Max amount of FITech students: 1 000 Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course. Our every-day lives are substantially affected by political decisions. These decisions are often based on the predictions of models that have been fit to data. As a case