Application deadline: January 31, 2026 CET.
Please use the application form below after reviewing the course information.
Do you ever feel overwhelmed in selecting which AI tools could be useful to support you in your daily work?
Large Language Models (LLMs) and Generative Artificial Intelligence (AI) provide unprecedented opportunities for research and business practice. However, there is a multitude of different tools that researchers theoretically can choose from.
This online course is dedicated to the use of AI-powered tools in research. It offers an overview of existing AI tools and how they can be integrated at different stages of research: project planning and organization, literature review, data analysis, and the reporting and communication of results. We will discuss the opportunities these tools provide but also their limitations and how to critically evaluate them. Finally, we will address ethical considerations and the current standards for transparently disclosing one’s own use of AI.
Topics
- Fundamentals of LLMs and AI Tools for Research, Including
- Effective Prompting Techniques
- Planning and Organizing Research Projects
- Literature Review & Management
- Data Collection & Analysis
- Organizing Research Projects and Communicating Results
- Limitations and Caveats of LLMs and Generative AI in Research: From Ethical Considerations to Scientific Best Practices
Format
This is an online course. The format will take place in two interactive workshop sessions, in which we will discuss fundamentals and applications of generative AI and LLMs in scientific research. In addition, we will work on several hands-on exercises to explore the opportunities and limitations of AI tools in research. From week 1 to week 2, participants will work on an own exercise related to using LLM tools for data collection and analysis.
- Week 1: Introduction into LLM and AI Tools, effective prompting strategies and caveats when using AI. We will also look into LLM tools for text and image generation, as well as applications of AI in data generation, collection, and analysis. The insights from this workshop session will be applied in a data collection and / or analysis task for session 2.
- Week 2: Discussion of own results related to a data collection and analysis task. Additionally, we will cover the selection and critical evaluation of AI tools and explore the options of LLMs for literature research and management.
Note: This course is not primarily about API handling for LLM tools (even though we will discuss this topic and you are free to explore it in your own exercise).
Meetings
The course includes 2 live online meetings, in which you will discuss the week’s contents with the instructor and fellow participants:
- Meeting 1: March 3, 2:00pm-5:00pm CET
- Meeting 2: March 10, 2:00pm-5:00pm CET
Prerequisites
- There are no pre-skills required
- Since we will be working hands-on with different AI tools, an account for one of the contemporary LLMs is advantageous (ChatGPT, Claude.AI, or Google Gemini).
- The willingness to setup new accounts for selected AI tools.
- A Zoom account.
Please note that this course presents both free and paid tools.
Application
The deadline to apply for this course is January 31, 2026 CET.
As the number of participants is limited, and to ensure the best fit between the course’s content and its participants, we will ask you to specify in the application form below why you would like to participate in this course. We will review all applications after the deadline and notify you of the outcome by mid-February.
The course is open to all researchers. However, as part of our role within the consortium for business, economics, and related data, priority will be given to researchers working in these fields.
The course is completely free of charge. As part of this opportunity, we kindly ask all participants to actively contribute to our evaluation process. This helps us to continuously improve the course.
About the Instructor
Melanie Clegg is Assistant Professor of Digital Marketing at HEC Lausanne, University of Lausanne. Her research addresses various aspects of digital marketing, from the use of artificial intelligence to social media marketing. It has been featured in leading marketing journals, including the Journal of Consumer Research, Marketing Letters, and the Harvard Business Review. Prior to joining HEC Lausanne, Melanie Clegg was an Assistant Professor at the Vienna University of Economics and Business (WU Vienna). Previously, Melanie Clegg completed her Ph.D. at the University of Lucerne in Switzerland and visited Columbia Business School.
