Course code DAT320

DAT320 Sequential and time series data analysis

Norsk emneinformasjon

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Showing course contents for the educational year 2022 - 2023 .

Course responsible: Oliver Tomic
Teachers: Stefan Schrunner, Kristian Hovde Liland
ECTS credits: 10
Faculty: Faculty of Science and Technology
Teaching language: EN
(NO=norsk, EN=Engelsk)
Teaching exam periods:
Autumn parallel
Course frequency: Yearly
First time: Study year 2022-2023
Course contents:

The course provides a theoretical and practical introduction to handling, processing, and analyzing data with dependence along one axis, such as sequential or time series data. The course focuses on applications from biology, industrial applications, and finance. The following topics will be covered:

  • preprocessing of time series data
  • stochastic processes and properties
  • forecasting of time series data
  • anomaly/outlier detection in time series data
  • classification/clustering in time series data

The course presents statistical and machine learning approaches. Students will learn to build effective and accurate models that, depending on the application, can contribute to several of UN's sustainability goals, among others 3, 11, 12, 14, 15.

Learning outcome:
Insight into relevant problems and models to analyze sequential and time series data from statistics and machine learning perspectives. Basic understanding of properties and definitions related to time series analysis. Practical hands-on experience in preprocessing, analyzing, and interpreting results for real-world datasets.
Learning activities:
LecturesCompulsory assignments with presentations (paper and pencil, programming)
Teaching support:
Supplementary online materialQ&A sessions with teaching assistants
Syllabus:
Announced in the lecture
Prerequisites:
Machine learning / statistics (DAT200 / STAT200)Introductory programming course (INF120 or similar)Basic calculus, linear algebra (MATH113 / 131 or similar)

Recommended prerequisites:
R programming (will be covered in the lecture, but basic knowledge is an advantage)
Mandatory activity:
Compulsory assignments with presentation sessions (mandatory attendance)
Assessment:
Written exam, 3.5 hours, grading: A-F
Nominal workload:
  • Lectures: 44h
  • Presentation sessions: 8h
  • Q&A sessions (not compulsory): 8h
  • Compulsory assignments, self-study & exam preparation: 190h
Type of course:
  • Lectures: 4h per week
  • Presentation sessions: 4 x 2-hour-sessions (dates will be announced)
  • Q&A sessions (not compulsory): 5 x 1.5-hour-sessions (dates will be announced)
Examiner:
An external censor will participate together with the internal censor in forming the exam and censor guide. The external censor checks the internal censor's assessment of a random selection of candidates as a calibration at certain intervals in line with the faculty's guidelines for censoring.
Allowed examination aids: A1 No calculator, no other aids
Examination details: Written exam: Letter grades