Course - Programming and Data in Business - IIRA2001
IIRA2001 - Programming and Data in Business
About
Examination arrangement
Examination arrangement: Portfolio
Grade: Letter grades
Evaluation | Weighting | Duration | Grade deviation | Examination aids |
---|---|---|---|---|
Portfolio | 100/100 |
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 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 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
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.
Recommended previous knowledge
Mathematics and Statistics as taught in the first year of relevant degree programmes.
Course materials
Announced at the start of term.
Credit reductions
Course code | Reduction | From | To |
---|---|---|---|
TDT4111 | 5.0 | AUTUMN 2023 | |
INGA1001 | 2.5 | AUTUMN 2023 | |
INGG1001 | 2.5 | AUTUMN 2023 | |
INGT1001 | 2.5 | AUTUMN 2023 | |
INGA1002 | 5.0 | AUTUMN 2023 | |
INGG1002 | 5.0 | AUTUMN 2023 | |
INGT1002 | 5.0 | AUTUMN 2023 |
No
Version: 1
Credits:
7.5 SP
Study level: Intermediate course, level II
Term no.: 1
Teaching semester: AUTUMN 2024
Language of instruction: Norwegian
Location: Ålesund
- Multidisciplinary Information and Communication Technology
- Computer Science
Department with academic responsibility
Department of ICT and Natural Sciences
Examination
Examination arrangement: Portfolio
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
-
Autumn
ORD
Portfolio
100/100
Release
2024-12-09Submission
2024-12-13
09:00
INSPERA
12:00 -
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"