Course - Programming and Data in Business - IIRA2001
IIRA2001
This course has academic overlap with the courses in the table above. If you take overlapping courses, you will receive a credit reduction in the course where you have the lowest grade. If the grades are the same, the reduction will be applied to the course completed most recently.
Programming and Data in Business
Credits
7.5
Level
Intermediate course, level II
Course start
Autumn 2026
Duration
1 semester
Language of instruction
Norwegian
Location
Ålesund
Examination arrangement
Portfolio
About
About the course
Course content
The module gives the student basic understanding of the use of modern, digital tools and methods to solve problems related to business administration. We address the following topics among others:
- Basic use of programming in business administration
- Concepts and terms which are used in information technology
- How to analyse large and fragmented data sets originating from different sources
- Visualisation of data as a means in communication and dissemination (customer data, accounting, logistics, etc)
- Understanding of information security
- Sources of information and data for analysis
- How artificial intelligence and machine learning can be used in business administration
Learning outcome
Knowledge
- The student is to know opportunities and limitations of programming and other digital tools (such as large language models) in the processing and analysis of business data.
- The student is to know the legal limitations for data processing.
Skills
- The student is to be able to use programming and digital tools (such as large language models) to simulate, model and solve problems in business administration and economics.
General Competency
- The student is to be able to communicate about computing tools, needs, and solutions across disciplinary boundaries.
- The student is to be able to use simulation and data analysis as a basis for business decisions
- The student is to be able to identify and assess information assets and security risks relating to data management.
Learning methods and activities
- Taught sessions with interactive and student active learning activities (e.g. live coding, group work)
- Practical exercises and projects under supervision by teaching assistants and module convener.
Compulsory assignments
- Exercises
Further on evaluation
(the information may be changed until June 15th)
Grading is based on the portfolio. Detailed requirements are announced at the start of term.
There is no re-sit examination. Candidates who fail, are absent, or who want to improve their grade, have to do the full portfolio the next time the module is taught. Mandatory coursework requirements are not carried over from previous years.
Course materials
Announced at the start of term.
Credit reductions
| Course code | Reduction | From |
|---|---|---|
| TDT4111 | 5 sp | Autumn 2023 |
| INGA1001 | 2.5 sp | Autumn 2023 |
| INGG1001 | 2.5 sp | Autumn 2023 |
| INGT1001 | 2.5 sp | Autumn 2023 |
| INGA1002 | 5 sp | Autumn 2023 |
| INGG1002 | 5 sp | Autumn 2023 |
| INGT1002 | 5 sp | Autumn 2023 |
| IIRA6001 | 7.5 sp | Autumn 2025 |
| IIRA2011 | 4 sp | Autumn 2026 |
Subject areas
- Multidisciplinary Information and Communication Technology
- Computer Science
Contact information
Course coordinator
Lecturers
Department with academic responsibility
Examination
Examination
Examination arrangement: Portfolio
Grade: Letter grades