T-122.101 Special Course in Information Science V L
Analysis of time-series and sequences
ANALYSIS OF TIME SERIES AND SEQUENCES
Large amounts of temporal data are available from various sources and can be analyzed in order to model the dynamics of the underlying system.
For instance, weather data, stock market prices, measurement data from industrial processes, telecommunications or ecological systems are examples of time series where the temporal structure of the data is important. On the other hand, data like DNA sequences or other symbolic sequences present sequential structure that can be used in the analysis of the phenomenon in question.
Two main themes that are covered on the course is prediction and model-based description of temporal and sequential data. Prediction will be presented in the context of continuous data, whereas the model-based description is mainly in the context of categorical time-series, or sequences. Time allowing, some hybrid modeling appraches will be included.
A more detailed motivation along with the course syllabus will be presented during the first lecture.
Selected scientific articles, textbooks and lectures will form the materials for the course. The lecture slides can be found on the Timetable page.
Timetable is available here.
To pass the course, one needs to
If one does all the work described above he or she will get 4 credits. If one don't like to do either presentetion or project work, he or she will get 3 credits.
The best way to contact the course staff is to come to the lectures. Second best way is to come and see course assistant before the lecture, on Tuesdays 12:00 to 14:00. Third, and the worst, way is with email to t122101@REMOVEME!james.hut.fi.
Thursday, 30-Sep-2004 15:18:17 EEST