LOG797 Data driven health Care and AI. (Spring 2026)

About the course

This course will introduce non-technical students to the world of applied artificial intelligence (AI) and empower them to understand and apply AI concepts to real-world problems. Through a blend of theoretical explanations, practical hands-on exercises, and engaging case studies, students will gain a comprehensive understanding of how AI is transforming various industries and will develop the skills to harness its power in their own careers or endeavors.

This course is designed for non-technical students, including those from business, humanities, and social sciences, who are interested in understanding and applying AI concepts in their fields. It is also suitable for individuals seeking to gain a broader understanding of AI and its potential impact on society and daily work tasks.

The course is connected to the following study programs

• Experience-based Master in Health Logistics - netbased

The student's learning outcomes after completing the course

Knowledge

The student should have advanced knowledge within:

• • • The concepts of AI and its impact on society and daily work tasks.

    • Recognize the applications of AI across various domains, including healthcare, logistics, finance, marketing, and education.

    • The ethical considerations and responsible use of AI in real-world settings. Responsible AI principles.

    • Apply AI tools and techniques to solve practical problems using Python, an accessible programming language.

    • Use and understand generative AI tools

    • Develop critical thinking and problem-solving skills through a series of hands-on projects

 

Skills

The student is able to:

• analyze and deal critically with various sources of information

• analyze existing theories and concepts using big data and AI

• work independently on practical and theoretical problem.

• can analyze and interpretate AI and data driven concepts on a practical level

 

General competence

After completing the course, the student can:

• • • • analyze relevant academic, professional and research ethical problems connected to AI and data driven decisions.

      • apply his/her knowledge and skills in new areas in order to carry out advanced assignments and projects

      • can communicate extensive independent work connected to AI and data driven healthcare.

      • can communicate about academic issues, analyses and conclusions in the field, with specialists

      • contribute to new thinking and innovation processes

Forms of teaching and learning

6 hours per week, teaching is twice a week for approximately two months.

Coursework requirements - conditions for taking the exam

None

Examination

Proportion: Two exams, one individual (40%) and one group exam (60%)

• Individual exam (40% of final exam): 1h, multiple choice. The student needs to pass to take the group exam. Grading : Letter A-F

• Group-exam (60% of final grade): Home exam, maximum number of students in a group : 4. Grading: Letter A-F

Syllabus

TBA