The course is included in these curricula and study modules
- Information technology 2014 - Machine learning and decision support system development
- Information technology 2015 - Machine learning and decision support system development
- Information technology 2017 - Machine learning and decision support system development
- Information technology 2018 - Machine learning and decision support system development
- Information technology 2019 - Machine learning and decision support system development
- Information technology 2020 - Machine learning and decision support system development
- Information technology 2021 - Machine learning and decision support system development - advanced studies
- Information technology 2022 - Machine learning and decision support system development - advanced studies
- Information technology 2023 - Machine learning and decision support system development - advanced studies
The course takes place in period
4 (2023-03-20 to 2023-07-31)
Level/category
Teaching language
Swedish
Type of course
Compulsory
Cycle/level of course
First
Recommended year of study
3
Total number of ECTS
5 cr
Competency aims
Within this study unity we will focus on the
following competences:
Applying machine learning as a method for data
management
Time series management and forecasting
Regression analysis
Learning outcomes
You are familiar with basic analytical terms
(knowledge)
You can interpreat and process input and output
data (skill)
You can process and analyze time series and
perform regression analysis (skill)
You are capable of solving specific problems where
supervised learning is used as training method for
creating forecasting models (färdighet)
Course contents
TIME SERIES
Loading and managing data
Feature engineering
Resampling
Visualization
Statistical models for forecasting
LINEAR REGRESSION
Data pre processing
Model creation
NEURAL NETWORK BASED MODELS FOR FORECASTING
Prerequisites and co-requisites
Statistics and probability
Data processing
Design of analytical systems
computer vision
Recommended or required reading
Material is 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
- Project work and presentation
Assessment requirements
Project work and participation in a project feedback
session.
Teacher
Dayama Niraj
Examiner
Karlsson Jonny
Home page of the course
Group size
No limit (30 students enrolled)
Assignments valid until
12 months after course has ended
Course enrolment period
2023-03-06 to 2023-04-02
Assessment methods
- Date will be announced later - Reports and productions
- 2022-03-28 - Other assignments
Date | Time | Room | Title | Description | Organizer |
---|---|---|---|---|---|
2023-04-03 | 14:00 - 16:00 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-04-05 | 14:00 - 16:00 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-04-12 | 14:00 - 16:00 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-04-14 | 12:00 - 14:00 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-04-17 | 09:30 - 11:30 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-04-19 | 14:00 - 16:00 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-04-24 | 09:30 - 11:30 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-04-24 | 12:00 - 13:00 | F365 | Gästföreläsning - Europeisk NLP data | Gästföreläsning med Andreas von Koskull Co-Founder & CEO Vox AI - Systematic Creativity in AI Speech Data | Dayama Niraj Karlsson Jonny |
2023-04-26 | 14:00 - 16:00 | E385 | Prediktiv analytik | Dayama Niraj | |
2023-05-03 | 14:00 - 16:00 | E383 | Prediktiv analytik | Dayama Niraj | |
2023-05-04 | 12:15 - 14:15 | E383 | Prediktiv analytik | Dayama Niraj | |
2023-05-08 | 09:30 - 11:30 | E383 | Prediktiv analytik | Dayama Niraj | |
2023-05-12 | 09:30 - 11:30 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-05-15 | 09:30 - 11:30 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-05-16 | 09:30 - 11:30 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-05-22 | 14:00 - 16:00 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-05-23 | 09:30 - 11:30 | F365 | Prediktiv analytik | Dayama Niraj | |
2023-05-24 | 13:15 - 14:00 | D4110 | Studentdialog för 3:dje årets IT-studenter | Biström Dennis Dayama Niraj Grönholm Hanna Karlsson Jonny Scherbakov-Parland Andrej Welander Fredrik |