Table of contents

The course is connected to the following study programs

  • Applied Artificial Intelligence 1, one-semester programme

Teaching language

English

Recommended previous knowledge

IKT116N Introduction to Artificial Intelligence

Learning outcomes

Upon successful completion of the course, students will be able to:

  • Identify various types of data and their relevance.
  • Analyze datasets to uncover insights.
  • Interpret AI-generated reports and predictions.
  • Apply data-driven strategies to support decision-making processes.

Contents

This course introduces students to the essential role of data in AI-driven decision-making. Students will explore how data is collected, cleaned, analyzed, and visualized, and they will learn to interpret and make sense of data trends and patterns. The course emphasizes how AI models use data to generate insights and predictions, with hands-on practice using no-code and low-code AI tools like Google AutoML and Microsoft AI Builder. By understanding how AI translates data into business intelligence, students will be able to make more informed and strategic decisions.

Teaching and learning methods

The course is given online and is organized in combination of lectures, assignments, paper studies, labs, report writing and self-study. The tasks are done individually or in small groups with group supervision. The workload for the average student is approximately 135 hours.

Examinations

Graded portfolio assessment, individually or in groups. Groups are given joint grades. Information about the content of the portfolio will be given in Canvas at the start of the semester.

Student evaluation

The person responsible for the course decides, in cooperation with student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.

Offered as a free-standing course

Yes
Last updated from FS (Felles studentsystem) Oct. 15, 2026 2:26:15 PM