Over the last few months, the rapid establishment of generative AI and Large Language Models (LLM) – such as ChatGPT – has opened new frontiers in a variety of domains.
This hands-on class aims to provide researchers in different scientific and disciplinary fields with the necessary skills to effectively use this cutting-edge technology in their academic research.
The class will cover different aspects of using ChatGPT, including the theoretical background and several examples of practical application in research, e.g. how to use ChatGPT to generate high-quality content for research papers, proposals, and grant applications.
The workshop is held in one day, divided into 2 sessions: the first one in the morning to provide the necessary elements for effective use of ChatGPT, the second one in the afternoon to apply what has been learned.
objectives
The class aims to show participants how to effectively integrate new generative AI tools within their research workflow. AI tools are not intended as substitutes, but rather as tools to support brainstorming, exploration, analysis and synthesis processes. Objectives include:
- Providing a background of the evolution of generative AI models
- Providing an overview of the features and capabilities of ChatGPT
- Analysing prompt engineering techniques for different purposes
- Exploring several applications of ChatGPT in academic research
- Providing hands-on experience with using ChatGPT for research purposes
- Critically evaluating the AI generated outcomes
who is this for?
The workshop is designed for PhD students and scholars who are approaching the use of new generative AI tools. Considering the high versatility of this new technology, the class is designed as an interdisciplinary initiative and is open to all researchers regardless of their scientific field.
No prior experience in machine learning or coding expertise is required.
schedule
MORNING
Introducing Generative AI
1.1. Brief historical background: from first AI to generative AI
1.2. Mapping generative AI tools
1.3. Focus on Large Language Models (LLMs)
1.4. ChatGPT and other competitors
How to Use ChatGPT
2.1. Prompt engineering
Generative AI in Business | Some examples
3.1. In Marketing: content generation, sentiment analysis, summarisation
3.2. In Product Development
3.3. In Art: generating images, music and videos
3.4. In Research: the topic of this class
AFTERNOON
ChatGPT in Research | Hands on Session | Write your Paper Using AI
4.1. Conducting a literature review
4.2. Finding research gaps
4.3. Doing qualitative research
4.4. Doing quantitative research (data analysis)
4.5. Generating code
4.6. Writing an article (storytelling, etc.)
4.7. Presenting the outcome
Discussion
5.1. Ethical considerations
5.2. Ownership, copyright and authenticit
ABOUT THE INSTRUCTOR
Francesco Ferrati holds a PhD in Management Engineering from the University of Padova. He is currently a researcher in Entrepreneurship at the Department of Industrial Engineering, DII – School of Entrepreneurship, SCENT. He teaches a Graduate Degree course in “Business Administration and Organization”. His research interests include the analysis of key success factors for tech-driven startups and equity investors’ decision-making processes. From a methodological perspective, he applies a strongly data-driven approach, based on the analysis of large business-related datasets through advanced data mining and machine learning techniques. He also has a general interest in artificial intelligence as a driver for new methodological approaches to Entrepreneurship.
