The course is included in these curricula and study modules

The course takes place in period

4 (2021-03-22 to 2021-07-31)

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
learns
to apply machine learning as a method for
processing data. The course focuses on the use
and treatment of time series data and then
perform regression analysis.

Learning outcomes

After completing the course, the student is
expected to be able to solve specific problems
where supervised learning is used as a training
method to create models that predict future
events.

Course contents

Analytical concepts
Interpretation and processing of input and output
Application of machine learning
Graphical representation of results

Prerequisites and co-requisites

The courses:
Data Processing and Data Science
Descriptive Analytics - Data/Text Mining
Computer vision

Additional information

The student should follow the announced time
frames
for the project, only in exceptional cases can
they
be changed.

Recommended or required reading

Provided through ItsLearning.

Study activities

  • Lectures - 30 hours
  • Individual- and group instruction - 30 hours
  • Project- and production work/artistic activities - 60 hours
  • Individual studies - 15 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 is required to
complete and present a project announced through
ItsLearning.

Teacher

  • Majd Amin
  • Scherbakov-Parland Andrej
  • Karlsson Jonny

Examiner

Westerlund Magnus

Home page of the course

Group size

No limit (42 students enrolled)

Assignments valid until

12 months after course has ended

Course enrolment period

2021-03-08 to 2021-04-04

Assessment methods

Date will be announced later - Reports and productions

Room reservations
Date Time Room Title Description Organizer
2021-03-24 10:00 - 12:30 Predictive Analytics Karlsson Jonny
Majd Amin
Scherbakov-Parland Andrej
2021-03-26 10:00 - 12:30 Predictive Analytics Majd Amin
Scherbakov-Parland Andrej
2021-03-31 10:00 - 12:30 Predictive Analytics https://arcada.zoom.us/j/66297974029?pwd=Qzl6ZVEzaElQSlZqb1BXeEJnV2pVdz09 Majd Amin
Scherbakov-Parland Andrej
2021-04-07 10:00 - 12:30 Predictive Analytics https://arcada.zoom.us/j/64224258803?pwd=bUdRWXlUankrTUMvTGd1Y3BpTlZzQT09 Majd Amin
Scherbakov-Parland Andrej
2021-04-09 10:00 - 12:30 Predictive Analytics https://arcada.zoom.us/j/66001933667?pwd=THRUakNaWWNjVTk5K0UrY0hVY0NVQT09 Majd Amin
Scherbakov-Parland Andrej
2021-04-14 10:00 - 12:30 Predictive Analytics - Coding session https://arcada.zoom.us/j/65044991281?pwd=OWFQZ2U2UWRhS3hWM3VqZFBYaWdrdz09 Majd Amin
Scherbakov-Parland Andrej
2021-04-16 10:00 - 12:30 Predictive Analytics - Coding session https://arcada.zoom.us/j/67363111085?pwd=b1J6UmgxZDdtaktYZ1hEbk9mQjZWdz09 Majd Amin
Scherbakov-Parland Andrej
2021-04-23 10:00 - 12:30 Predictive Analytics - Coding support https://arcada.zoom.us/j/65800256306?pwd=bVg4MmpZL1VFck5rZ3VLMTk1V1RzUT09 Majd Amin
Scherbakov-Parland Andrej
2021-04-29 10:00 - 12:30 Predictive Analytics - Project presentations https://arcada.zoom.us/j/65800256306?pwd=bVg4MmpZL1VFck5rZ3VLMTk1V1RzUT09 Scherbakov-Parland Andrej

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