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Artificial intelligence (5 cr)

Code: LO00EB70-3002

General information


Enrollment
07.11.2022 - 18.11.2022
Registration for the implementation has ended.
Timing
16.01.2023 - 28.04.2023
Implementation has ended.
Number of ECTS credits allocated
5 cr
Local portion
5 cr
Mode of delivery
Contact learning
Unit
Department of Logistics and Marine Technology
Campus
Kotka Campus
Teaching languages
English
Seats
20 - 40
Degree programmes
Degree Programme in Logistics
Teachers
Eeva Ala-Krekola
Teacher in charge
Eeva Ala-Krekola
Groups
LLKT22SD
Double Degree in Business Logistics
LOKT22SD
Double Degree in Logistics Engineering
LOKT20SP
Logistics, full-time studies
Course
LO00EB70
No reservations found for realization LO00EB70-3002!

Objective

You understand what artificial intelligence is and what opportunities and changes it may bring, especially in the field of logistics.
You understand the advantage of artificial intelligence and its potential when applied to logistic processes.

Content

Is artificial intelligence a threat or an opportunity?
How will artificial intelligence and machine learning change the world and ways of working?
In what ways and in what applications can artificial intelligence be utilized?
How can human beings and artificial intelligence cooperate in the same job?

Evaluation

Students are able to
- 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

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Study forms and methods

If the student wishes to follow an individual learning track, the student writes a plan for the individual learning track. The plan must comply with the learning outcomes of the course and has to be approved first by the teacher of the course and then by the student's work place. The individual learning track must be agreed with the teacher prior to the course start.

Timing of exams and assignments

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Student workload

5 cr / 135 h

Evaluation scale

1-5

Assessment methods and criteria

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