IA-2-008

• Information technology 2014 - Analytical methods and data science
• Information technology 2015 - Analytical methods and data science
• Information technology 2016 - Analytical methods and data science
• Information technology 2017 - Analytical methods and data science
• Information technology 2018 - Web and visualization
• Information technology 2019 - Web and visualisation
• Information technology 2020 - Web and visualization
• Information technology 2021 - Web and visualisation - foundation studies
• Information technology 2022 - Web and visualisation - foundation studies
• Information technology 2023 - Web and visualisation - foundation studies
• Business administration 2014 (logistics) - Web and visualization ii
• Business administration 2014 (marketing) - Web and visualization ii
• Business administration 2014 (tourism) - Web and visualization ii
• Business administration 2015 (logistics) - Web and visualization ii
• Business administration 2015 (marketing) - Web and visualization ii
• Business administration 2015 (tourism) - Web and visualization ii
• Business administration 2016 (logistics) - Web and visualization ii
• Business administration 2016 (marketing) - Web and visualization ii
• Business administration 2016 (tourism) - Web and visualization ii
• Information- and mediatechnology 2012 (media technology) - Web technology
• Information- and mediatechnology 2013 (media technology) - Web technology

4 (2023-03-20 to 2023-07-31)

Swedish

Compulsory

First

2

5 cr

Different kinds of charts for information
visualization.

Programming technologies for creating charts (e.g.
D3.js)

You understand how different charts can be used
for different kinds of information (knowledge)

You can utilize D3.js or similar technologies for
creating charts in a web context (skill).

You understand how interactivity can improve
information accessibility (attitude).

Data visualization on Websites with the Data-
Driven Documents library D3.js:
- Line charts
- Dot charts
- Histograms
- Network graphs

Introduction to data visualization using Python
and Matplotlib.

Web Development
Front-end programming
Statistics and probability

• Lectures - 33 hours
• Individual studies - 102 hours

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

Participation in tuition

Projects, quizzes and exercises.

Dayama Niraj

Karlsson Jonny

https://arcada.itslearning.com/ External link

No limit (29 students enrolled)

12 months after course has ended

2023-03-06 to 2023-04-02

Date will be announced later - Other assignments