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Fundamentals of Data processing and Programming for Artificial Intelligence , 15 Credits

Grunder i databehandling och programmering för artificiell intelligens, 15 Högskolepoäng

Established: 2026-05-27

Established by: School of Business, Economics and IT

Applies from: V27

Learning outcomes

After completing the course, the student should be able to:

1. Knowledge and Understanding

1.1 Describe the fundamentals of data processing, including data collection, data analytics and data modelling.

1.2 Describe common data types, data structures, and data representations used in AI and data processing applications (including structured, semi-structured, and unstructured data).

1.3 Describe and demonstrate fundamental programming principles.

2. Skills and Abilities

2.1 Apply basic programming techniques to read, process, transform, analyze and visualize data.

2.2 Use descriptive analytical methods to explore datasets to identify patterns, trends, and anomalies.

2.3 Plan a small-scale data processing project by defining objectives, identifying required data, selecting appropriate methods, and organizing work activities.

3. Judgement and Approach

3.1 Reflect on the quality, limitations, and potential biases of data used for data processing and in AI systems

3.2 Evaluate the applicability and relevance of a given tool or method for data processing under given circumstances

3.3 Reflect on the ethical implications and dimensions of data collection

3.4 Reflect on one’s learning and knowledge development regarding data processing.

Entry requirements

General entry requirements.

You also need: English 6, Mathematics 2a or Mathematics 2b or Mathematics 2c, and Social Studies 1b or Social Studies 1a1 and 1a2.

Or: English Level 2, Mathematics Level 2a or Mathematics Level 2b or Mathematics Level 2c, and Social Studies Level 1b or Social Studies Level 1a2.

The forms of assessment of student performance

The course is examined through:
Written exam
Group work including oral presentation

Course contents

The course offers an introduction to central concepts in data processing and basic programming concepts related to AI. This includes the fundamentals of data science, data types, data representation, statistics, and data preprocessing.

To enable practical application of these theories and methods, basic programming skills are introduced.

The course also covers basic methodologies for project management and organisation in programming and data processing projects, including version control, file repositories, and progress tracking.

Overall, the course aims to provide a technical and conceptual foundation upon which later courses can build. The concepts introduced in this course will support the understanding of more advanced topics such as machine learning, data processing, data visualisation, and various AI tools.

Other regulations

Course grading: F/Fx/E/D/C/B/A - Insufficient, Insufficient- more work required before the credit can be awarded, Sufficient, Satisfactory, Good, Very Good, Excellent

Course language: The teaching is conducted in English.

University West’s regulations on grading systems for first, second and third‑cycle education as well as general rules pertaining to examination are available at www.hv.se.

If the student has a decision/recommendation on special support due to disability, the examiner has the right to examine the student in a customized examination form.

Cycle

First cycle

Progressive specialization

G1N - First cycle, has only upper-secondary level entry requirements

Main field of study

Informatics