Context

Here is some useful background knowledge about the new course:

Course:

• Teaching language is English
• We can expect 8-24 students per year (last year around 22, this year 16)
• The course is part of an ICT education. The students will expect to learn ICT theory and practice ICT skills, along with the EM theory and skills.
• This is a research master course. The title is research topics in Big Data, and a primary goal is to set up the students for doing their supervised research master thesis work.

Students:

• Most students will be in their first year of a 2-year master. They will usually be in their 4th year of study.
• Most of them will be information science students (basic ICT, with slightly more user/organisation/society emphasis).
• Some of them will also have purer computer science or new media backgrounds (lighter on ICT).
• We require some knowledge of how to program, and most of the students will have had several courses involving programming).
• Most used programming language is Python, but you can decide what you want to use other than Python.
• Some of the students will have had UX design and semantic technology courses, but we do not yet offer pure big data or machine-learning courses.
• On master levels, there are other dedicated HCI, ML and AI courses, so we do not have to (and perhaps should not) cover that in depth.

Semester outline:

• The course constitutes 50% of a semester.
• The autumn semester runs from around August 15th until late November. December is for finishing projects and exams.
• The autumn semester is around 14 weeks long.
• Usually, the students meet for a whole day (1015 to 1600) every other week. This is called a session.
• There are around 7 sessions in a semester.
• In each session, we can perhaps cover two central themes + simple exercises, or one central theme + an exercise.
• We require 80% attendance to pass the course.
• We can perhaps add a few extra activities outside the regular schedule, but they have to be planned many months before, before the student's schedules are tight (they have mandatory activities in other courses, work as teaching assistants, etc.)
• If we add extra activities, it is easier if we make them voluntary.

Session outline:

• Sessions run from 1015 until at least 1600. Until 1600ish is possible when there are practical exercises to do.
• We try to combine ordinary lectures, prepared student presentations, quizzes using Kahoot (for example - you will need to create an account), technical demonstrations, and hands-on exercises.
• Students will bring their laptops.

Requirements to pass:

• 80% attendance in the around 7 mandatory sessions is required (you cannot be away for more than 1 1/2 session).
• An individual essay on a self-selected and approved them (typically 8-15 pages).
• A programming project in groups of 4 on a self-selected and approved task, including a very compact 2-page report.
• A 3 hour exam in December.