Creating Business Value with Generative AI

English language course for business students at Aarhus University

• Course Catalogue: Creating Business Value with Generative AI
• Lecturers: Arthur Hjorth, Magnus Bender

Content

This course aims to equip students with a blend of theoretical knowledge, practical skills, and the competencies needed to navigate and exploit the opportunities presented by Generative AI in the business world.

Knowledge

• Understanding of Generative AI: Students will have a broad understanding of Machine Learning and Generative AI with particular focus on large language models (LLMs), and the ability to explain how Generative AI works.
• Theoretical Basis for Business Value: Students will understand the theoretical arguments for the potential business value created by applications developed with Generative AI.
• Viable and Relevant Business Cases for Generative AI: Students will have a broad understanding of the various ways in which Generative AI can contribute to value creation in business.
• Model Selection and Validation: Students will acquire knowledge of various local and proprietary models, including criteria for choosing the right model for a specific business use case and methodologies for testing and validating model performance.

Skills

• Coding: Ability to code, especially for individuals with no prior coding experience, including the development of simple web apps that implement practical applications of Large Language Models.
• Analytical Skills: Skills in systematically selecting, testing, and validating sufficiently good models for specific purposes.
• Creative and Communicative Skills: Ability to creatively and practically apply Generative AI solutions in business contexts and effectively communicate theoretical and practical insights.

Competencies

• Practical Applications of Generative AI in Workplaces: The capability to apply acquired knowledge and skills in real-world business settings, leveraging Generative AI to create value.
• Identifying and Solving Business Problems: Competency in identifying and effectively addressing business challenges that Generative AI can add value to.

Lectures

1. Introduction to Course
2. Machine Learning and LLMs (pdf, pdf no animations)
3. Business Process Redesign
4. LLMs and Value Creation
5. NLP tasks with LLMs (pdf, pdf no animations)
6. Prompting and Prompting Techniques
7. LLM Reasoning
8. Qualitative Methods with LLMs
9. Advanced uses of LLMs (pdf, pdf no animations)
10. Hallucinations
11. Validating Model Output
12. Summary and Generative AI in Future Work
13. Ethics, AI and the Law (pdf, pdf no animations)

Tutorials

Only some provided here.

• More Python and Coding (pdf, pdf no animations)
• Use LLMs to Structure Data (pdf, pdf no animations)
• Advanced Uses of LLMs & Python Packages (pdf, pdf no animations)
• Recap on Validation (pdf, pdf no animations)

Study Programs

• Elective for Bachelor’s Degree Programme in Economics and Business Administration
• Elective for Bachelor’s Degree Programme in Business Administration and Commercial Law

Workload und Examination

• Workload
  • 10 ECTS
  • Weekly lecture of 90 minutes
  • Weekly tutorial of 90 minutes
• Examination
  • Realization of a project applying GenAI to innovate a business process. Students analyze the process, create a prototype with an web-based interface, and conduct a validation.
  • Take-home assignment, final report and project’s code

Semesters

• Fall 2025