Level/category

Professional studies

Teaching language

English

Type of course

Compulsory

Cycle/level of course

First

Recommended year of study

3

Total number of ECTS

5 cr

Competency aims

The aim of the course is that the student knows common AI methods for analysing historical data. Another aim is to make student capable of finding AI opportunities in different business domains.

Learning outcomes

The student should be able to ask managerial questions that can be answered through the use of AI methods based on machine learning. Student has a fair understanding of the field of data science and how business value can be created through data analysis.

Course contents

Machine learning objectives for: -classification -regression -natural language processing. Introduction to python programming

Prerequisites and co-requisites

Module 1 or equivalent

Additional information

Have to pass the Mooc course Elements of AI @ HU

Recommended or required reading

Mooc course Elements of AI @ HU and others

Study activities

  • Lectures - 20 hours
  • Project- and production work/artistic activities - 65 hours
  • Internet-based studies - 50 hours

Workload

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

Mode of Delivery

Participation in tuition

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. Have to pass the Mooc course Elements of AI @ HU.

Teacher

Björk Kaj-Mikael

Examiner

Björk Kaj-Mikael

Home page of the course

https://arcada.itslearning.com/

Group size

No limit

Assignments valid until

12 months after course has ended

Assessment methods

Date will be announced later - Reports and productions

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