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Predictive analytics (5 cr)

Code: DA00EK62-3002

General information


Enrollment
08.04.2024 - 21.04.2024
Registration for the implementation has ended.
Timing
02.09.2024 - 31.12.2024
Implementation has ended.
Number of ECTS credits allocated
5 cr
Local portion
0 cr
Virtual portion
5 cr
Mode of delivery
Distance learning
Unit
Department of Business
Campus
Kouvola Campus
Teaching languages
Finnish
Seats
20 - 60
Degree programmes
Degree Programme in Data Analytics
Teachers
Atte Reijonen
Jarkko Ansamäki
Teacher in charge
Jarkko Ansamäki
Groups
DAKV22SM
Data analytics, part-time
Course
DA00EK62

Realization has 5 reservations. Total duration of reservations is 7 h 30 min.

Time Topic Location
Fri 13.09.2024 time 12:50 - 14:20
(1 h 30 min)
Ennakointi DA00EK62-3002
Etäopetus lukujärjestyksen mukaan
Fri 11.10.2024 time 12:50 - 14:20
(1 h 30 min)
Ennakointi DA00EK62-3002
Etäopetus lukujärjestyksen mukaan
Fri 08.11.2024 time 12:50 - 14:20
(1 h 30 min)
Ennakointi DA00EK62-3002
Etäopetus lukujärjestyksen mukaan
Fri 29.11.2024 time 09:00 - 10:30
(1 h 30 min)
Ennakointi DA00EK62-3002
Etäopetus lukujärjestyksen mukaan
Fri 29.11.2024 time 10:40 - 12:10
(1 h 30 min)
Ennakointi DA00EK62-3002
Etäopetus lukujärjestyksen mukaan
Changes to reservations may be possible.

Objective

You understand the principles of futurology.
You understand when and how to predict the future based on existing data.
You can create mathematical models for forecasts.
You can write future-oriented reports.

Content

What different methods can be used to study the future?
How can trends be drawn from existing data to predict future values for the data?

Evaluation

Students can
use professional vocabulary and concepts in an expert way in different situations.
evaluate information sources critically.
work as team members in working life expert duties and identify and describe the problems of the professional field.
evaluate operations in customer, user and target group situations.
choose appropriate models, methods, software and techniques according to the purpose and justify these choices.
promote teams’ goal-oriented operation.
apply critically the ethical principles of the professional field in different situations

Course material

Web materials

Study forms and methods

Individual learning tracks should always be discussed with the lecturers

RDI and work-related cooperation

The course may have assignments made for companies or assignments agreed individually with students.

Student workload

1 cr = 27 hours work

Evaluation scale

1-5

Assessment methods and criteria

There are multiple lecturers in the course and final evaluation is based on the individual evaluations of the lecturers and the evaluation of the final project(s)

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