Business Insights with Al (E)
| Course unit title | Business Insights with Al (E) |
| Course unit code | 025008042223 |
| Language of instruction | English |
| Type of course unit (compulsory, optional) | Elective |
| Teaching hours per week | 30 |
| Year of study | 2026 |
| Number of ECTS credits allocated | 3 |
| Name of lecturer(s) | Eric KYPER |
| courseEvent.detail.semester | |
| Degree programme | International Business |
| Subject area | Business and Management |
| Type of degree | Bachelor full-time |
| Type of course unit (compulsory, optional) | Elective |
| Course unit code | 025008042223 |
| Teaching units | 30 |
| Year of study | 2026 |
| Name of lecturer(s) | Eric KYPER |
None
- Data Mining
- Data Advantages
- AI tools for business advantages
- Security and societal as well as legal aspects related to big data collection and analysis
- Business implications of trends in operational data processing.
Data is commonly referred to as the "oil of the 21st century". In many cases, the use of data is a source of significant earnings potential and competitive advantages. Recognizing the potential rewards inherent in data and information systems is of great value.
Now that AI is dominating nearly all aspects of data analysis, business intelligence, and many other aspects of core business functions, this course will help identify opportunities, and teach how to prompt AI to leverage said opportunities.
Students will recognise general data mining techniques. They recognise threats to business security and identify business continuity requirements and backup plans in case of data loss. Students understand the primary objectives of Big Data and the associated potential benefits. Students will be able to perform a cost / benefit analysis of big data systems.
Interactive course with lecture, case studies, exercises in individual and group work, presentations and homework.
Pre-assignment, participation during the seminar in the form of contributions and short presentations (individual or group assignments), post-assignment, individual weighting as determined by the instructors, announcement at the beginning of the semester
None
McKinsey & Company (2023) "The Economic Potential of Generative AI: The Next Productivity Frontier" - Shows AI could deliver $4.4 trillion in productivity gains, with 20-45% efficiency gains in software engineering and 10-15% in R&D (https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work)
Brynjolfsson, Li & Raymond (2023): "Generative AI at Work" - Found AI improved productivity by 66% averaged across three studies, with customer service agents handling 13.8% more inquiries per hour AI Improves Employee Productivity by 66% (https://www.nngroup.com/articles/ai-tools-productivity-gains/)
Noy & Zhang (2023): "Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence" - Business professionals wrote 59% more documents per hour with AI assistance (https://www.stlouisfed.org/on-the-economy/2024/apr/ai-productivity-growth-evidence-historical-development-other-technologies)
Classes with compulsory attendance