The course is included in these curricula and study modules

The course takes place in period

4 (2024-03-18 to 2024-07-31)

Level/category

Professional studies

Teaching language

English

Type of course

Compulsory

Cycle/level of course

Second

Recommended year of study

1

Total number of ECTS

5 cr

Competency aims

The aim is to make student capable of finding AI
opportunities in different domains.

Learning outcomes

Knowledge
The student should be able to ask managerial and
specific questions that can be answered through
the use of AI methods based on machine learning.
Student can implement a project of its own in the
field of big data analytics.

Course contents

The students develop an understanding for
planning the analytical process; data-related
requirement handling, domain knowledge/modelling
expertise and verification of results. Each student
completes an industry cap-stone project as part of
the course.

Prerequisites and co-requisites

None

Study activities

  • Lectures - 20 hours
  • Individual- and group instruction - 10 hours
  • Project- and production work/artistic activities - 80 hours
  • Internet-based studies - 25 hours

Workload

  • Total workload of the course: 135 hours
  • Of which autonomous studies: 135 hours
  • Of which scheduled studies: 0 hours

Mode of Delivery

Multiform education

Assessment methods

Essays, reports, productions and portfolio

Assessment requirements

To pass the course the student must participate
and do the assignments given during the course.

Teacher

  • Björk Kaj-Mikael
  • Espinosa Leal Leonardo
  • Scherbakov-Parland Andrej
  • Westerlund Magnus

Examiner

Westerlund Magnus

Home page of the course

Group size

No limit (31 students enrolled)

Assignments valid until

12 months after course has ended

Course enrolment period

2023-11-24 to 2023-12-22

Assessment methods

Date will be announced later - Reports and productions

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