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DAT390 Data science seminar

Credits (ECTS):5

Course responsible:Martin Thomas Horsch

Campus / Online:Taught campus Ås

Teaching language:Engelsk, norsk

Course frequency:Annually

Nominal workload:Seminar meetings 13 hours; mentoring/datalab 12 hours; 100 hours self-study

Teaching and exam period:

The course starts in the autumn parallel.

Teaching and assessment are done in the autumn parallel.

About this course

The students acquire knowledge about current topics in data science through individual work, including the study of scientific publications, recent monographies, analysis projects or other suitable methods. They systematise and share the knowledge in oral and written form.

Learning outcome

You acquire in-depth knowledge about a specific topic in data science, you learn to present knowledge in written and oral form according to the standards of the field, and will gain an overview of current developments in data science.

  • Independent study of relevant material with mentoring as well as presentation for (and discussion with) fellow students. The students choose a topic the latest by the start of the course, preferably relevant for their master thesis. The students prepare a presentation and a written report on the topic, and present the presentation to their fellow students. The students attend the presentations and scientific discussions following the presentations.

    Recommendation: Do discuss the choice of topic and its relevance with your prospective Master thesis advisor beforehand.

  • Online learning resources will be connected to lectures and exercises through the course webpages in Canvas. The writing center can be utilised as a support during the writing process. The students get an introduction to making presentations and written material, how to refer to published material and re-use of material. The students get comments on a draft report and a nearly finished report.

  • DAT200, INF200, INF221, INF230, MATH280

    DAT300 can be taken simultaneously

  • The grade in the course is set on the basis of a term paper. Letter grades (A-F).

  • External sensor to be used only if (and to the extent) mandated by law pursuant to uhl. § 3-9.
    • Contribution to academic discussion (at seminar meetings)
    • Oral presentation

    Presentation and contribution to academic discussion must be passed.

  • This course is offered to students who are going to write a master thesis oriented towards data science during the following spring term.

  • 13 x 1 hour seminar meeting

    12 x 1 hour datalab/structured advisory time

  • REALFAG