Course wiki for INFO319: Difference between revisions

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''INFO319 is being redesigned. More information will appear here closer to the autumn semester 2022.''
This wiki (under development) contains practical information about INFO319 - Big Data in the autumn of 2022, including readings and exercises.


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* [[Sessions]]: The course comprises 8 full-day seminars. The sessions involve lectures, demos, student presentations, and practical work. Participation in 80% of course seminars is mandatory.
The course plans will be further detailed and more readings added throughout the semester.
* [[Readings]]: Course book and further readings for each session.
* [[Exercises]]: Exercises related to the sessions. Solutions to the exercises can form the backbone of the mandatory group assignment.
* [https://www.uib.no/emne/INFO319?sem=2022h Assessment]: The assessment has three parts:
** Portfolio evaluation (55%) in two parts:
*** An individual, theoretical essay with thoughtful research and discussion of an assigned topic
*** Practical assignment in groups
** Oral presentations of essay and group assignment (15%)
** Written exam (3 hours) (30%)
* [[Essay]]: Information about essay.
* [[Group assignment]]:
 
Information about the group assignment (a programming project that can be based on the exercises).
<!-- * [[Datasets]] : Available datasets that can be used for data analysis.
* [https://mitt.uib.no/courses/37204/pages/info319-big-data-h22 Administrative/formal]:
For formal and administrative information, see [https://mitt.uib.no/courses/37204/pages/info319-big-data-h22 UiB's Study Portal (http://mitt.uib.no/info319)].


* [[Sessions]]: Information about sessions covered in the course.
* [[Readings]]: Information about books and articles used in the course.
* [[Essay]]: Information about essay.
* [[Student project]]: Information about the student programming project.
* [[Tools]]: Which tools should we include/teach/introduce as part of the course?
* [[Exercises]]: Proposals for exercises to run as part of the course, tied to the course themes and preferably using the tools, as well as which data to run the exercises on.
* [[Literature]]: Proposals and ideas for literature we can use in the course - preferably explicitly tied to the themes.
* [[Datasets]] : Available datasets that can be used for data analysis.


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Revision as of 12:43, 5 July 2022

This wiki (under development) contains practical information about INFO319 - Big Data in the autumn of 2022, including readings and exercises.

  • Sessions: The course comprises 8 full-day seminars. The sessions involve lectures, demos, student presentations, and practical work. Participation in 80% of course seminars is mandatory.
  • Readings: Course book and further readings for each session.
  • Exercises: Exercises related to the sessions. Solutions to the exercises can form the backbone of the mandatory group assignment.
  • Assessment: The assessment has three parts:
    • Portfolio evaluation (55%) in two parts:
      • An individual, theoretical essay with thoughtful research and discussion of an assigned topic
      • Practical assignment in groups
    • Oral presentations of essay and group assignment (15%)
    • Written exam (3 hours) (30%)
  • Essay: Information about essay.
  • Group assignment:

Information about the group assignment (a programming project that can be based on the exercises).

 

Contact: Andreas.Opdahl@uib.no