UniOGS AI introduction, 1 ECTS credit
The UniOGS AI introduction course will give an introduction to AI for students that want to get the basics of the topic. The aim of the course is to discover problems in students own field of science that could benefit from the AI approach. The course starts with kick-off lectures that introduce several research themes applying AI. The lectures will be given by AI experts from different fields. During the workshop day, the students will map real data-intensive problems from their own field of science and process them in groups. The final ideas will be presented in the poster session. The course is suitable for all students in UniOGS.
20.8.2019 Kick-off lectures (Place: Tellus stage)
9:15-9:20 Opening, University of Oulu Graduate School Vice-Dean Jouko Miettunen
9:20-10:15 Introduction and history of AI, Arto Klami, Finnish Center for Artificial Intelligence (FCAI)
10:30-11:15 Role of data in machine learning and AI, Satu Tamminen, University of Oulu
11:15-12:00 Emotion AI, Guoying Zhao, University of Oulu
12:00-12:45 LUNCH BREAK
12:45-13:00 Medical AI, Simo Saarakkala, University of Oulu
13:00-13:45 Machine Vision and AI, Olli Silvén, University of Oulu
13:45-14:00 WRAP-UP and home assignments
21.8.2019 Workshop (Time 9-14 pm, Place: AT115A)
The purpose of this workshop is to map real data-intensive problems in each students’ own field of science. The home assignments given on 20th aims towards defining a suitable problem topic. This topic is then discussed in the work group. Each student will present their ideas to other students and assistants (5 min + discussion).
Questions: What kind of phenomena produces digital data in your own research field? Do you already possess data from some interesting phenomena in your research field?
In the group: What kind of similarities can be identified within the ideas given by students?
Discussion about: role of AI, automatic decision making, automatic analysis, prediction, situation awareness
3.9.2019 Poster session (Time 9-12 pm, Place: TA105)
The ideas are further developed, collaboration within and outside profiling areas are discussed, possible funding ideas are discussed.
In order to pass the course, the student must attend all three events and present the poster.
Responsible teacher for the course: Susanna Pirttikangas
Last updated: 9.8.2019