The course is included in these curricula and study modules
The course takes place in period
3 (2021-01-01 to 2021-03-21)
Level/category
Teaching language
English
Type of course
Compulsory
Cycle/level of course
Second
Total number of ECTS
5 cr
Competency aims
The aim of the course is...
Learning outcomes
At the end of the course the student is expected
to
be able to...
Course contents
The students learns to handle massive data
programmatically to perform feature
engineering.
The students understand how to employ both
classification and clustering algorithms for
big
data problems and how to utilize their output
in
service creation. Students learn to carry out
verification of results as part of the solution
process.
Mode of Delivery
Multiform education
Assessment requirements
To pass the course the student should pass the
following examinations:
Examination 1 ....
Examination 2.... etc.
(examinations include written examination
tests,
demonstrations and presentations, reports and
produktions, essays, and also presence at
specified occasions)
The examinations contribute to the final grade
as follows: ...
Teacher
- Espinosa Leal Leonardo
- Majd Amin
- Scherbakov-Parland Andrej
Examiner
Espinosa Leal Leonardo
Home page of the course
Group size
No limit (72 students enrolled)
Assignments valid until
12 months after course has ended
Course enrolment period
2020-12-24 to 2021-01-20
| Date | Time | Room | Title | Description | Organizer |
|---|---|---|---|---|---|
| 2021-01-21 | 13:00 - 18:00 | F249 | Machine Learning for Descriptive Problems | Espinosa Leal Leonardo | |
| 2021-01-22 | 13:00 - 18:00 | B518 | Machine Learning for Descriptive Problems | Espinosa Leal Leonardo | |
| 2021-02-04 | 13:00 - 18:00 | F249 | Machine Learning for Descriptive Problems | Espinosa Leal Leonardo | |
| 2021-02-05 | 13:00 - 18:00 | F249 | Machine Learning for Descriptive Problems | Espinosa Leal Leonardo |