DM566: Data mining and machine learning (10 ECTS)
STADS: N330039101Level
Teaching period
Teacher responsible
No responsible teachers found, contact the department if necessary
Timetable
| Group | Type | Day | Time | Classroom | Weeks | Comment |
|---|---|---|---|---|---|---|
| Common | I | Monday | 12-14 | U140 | 6-7,11 | |
| Common | I | Monday | 12-14 | U20 | 8-9,12 | |
| Common | I | Monday | 12-14 | U47 | 10 | |
| Common | I | Monday | 12-14 | U170 | 14 | |
| Common | I | Monday | 12-14 | U23 | 15,18,20 | |
| Common | I | Monday | 12-14 | U150 | 21 | |
| Common | I | Tuesday | 08-10 | U140 | 6,10 | |
| Common | I | Tuesday | 09-11 | U181 | 7 | |
| Common | I | Tuesday | 08-10 | U20 | 8 | |
| Common | I | Tuesday | 09-11 | U20 | 9 | |
| Common | I | Tuesday | 09-11 | U23 | 11,13,20 | |
| Common | I | Tuesday | 09-11 | U48A | 12,15 | |
| Common | I | Tuesday | 09-11 | U133 | 14 | |
| Common | I | Tuesday | 08-10 | U55 | 18 | |
| Common | I | Tuesday | 08-10 | U150 | 21 | |
| Common | I | Friday | 14-16 | U55 | 13 | |
| H1 | TE | Monday | 12-14 | U23A | 13 | |
| H1 | TE | Monday | 12-14 | U176 | 22 | |
| H1 | TE | Wednesday | 16-18 | U172 | 17 | |
| H1 | TE | Wednesday | 08-10 | U170 | 20 | |
| H1 | TE | Wednesday | 14-16 | U171 | 21 | |
| H1 | TE | Thursday | 16-18 | U31 | 8-9 | |
| H1 | TE | Thursday | 16-18 | U156 | 10,18-19 | |
| H1 | TE | Thursday | 16-18 | U48 | 15 | |
| H1 | TE | Friday | 14-16 | U154 | 6-7,11 | |
| H1 | TE | Friday | 14-16 | U155 | 12 | |
| H1 | TE | Friday | 14-16 | U166 | 14 | |
| H2 | TE | Tuesday | 09-11 | U156 | 17 | |
| H2 | TE | Tuesday | 09-11 | U176 | 22 | |
| H2 | TE | Wednesday | 16-18 | U155 | 20 | |
| H2 | TE | Thursday | 16-18 | U154 | 6-7,11,14 | |
| H2 | TE | Thursday | 16-18 | U156 | 12 | |
| H2 | TE | Thursday | 16-18 | U151 | 13 | |
| H2 | TE | Thursday | 10-12 | U175 | 21 | |
| H2 | TE | Friday | 14-16 | U156 | 8,10,18-19 | |
| H2 | TE | Friday | 14-16 | U30 | 9 | |
| H2 | TE | Friday | 14-16 | U154 | 11 | |
| H2 | TE | Friday | 14-16 | U155 | 15 |
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Prerequisites:
None
Academic preconditions:
None
Course introduction
Expected learning outcome
Subject overview
Literature
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Website
This course uses e-learn (blackboard).
Prerequisites for participating in the exam
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Assessment and marking:
Expected working hours
The teaching method is based on three phase model.
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Course enrollment
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Tuition fees for single courses
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