Course wiki for INFO319

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This course plans will be further detailed and more readings added throughout the semester.

  • 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.



Some background for the new course:

  • Course description: The formal description of the course as it currently appears in the university course list.
  • Context: Practical settings and formal requirements for the course, including the student's backgrounds, session lengths, semester outline, etc.


The course will build on the introductory and intermediate courses in big data technologies. If you register for the course without practical / programming skills, you are responsible for picking up the necessary background knowledge and skills on your own.


You must attend 80% of the course sessions, and you must submit a written individual essay and a student group project by the given deadlines. Two of the sessions, the essay presentations on Thursday 2020-11-26 and programming project presentations on Friday 2020-11-27, are mandatory.

Exam information


Associate Professor Vimala Nunavath ( will lead the course in the autumn of 2020. For questions that are not strictly personal, always use the discussion forum (requires login) at If I receive general questions about INFO319 by email, I will answer them in the forum anyway, so it is fastest to post them directly there.