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GenAI and Prompt engineering for scientific Research

GenAI and Prompt engineering for scientific Research

  • Université de Montpellier

Delivery institution

  • Université de Montpellier
Doctoral College

Instructor(s):

Maria Claudia Angel Ferrero

Start date

3 April 2025

End date

3 April 2025

Study field

  • Information and Communication Technologies

CHARM priority field

  • Transversal Skills

Study level

  • PhD

Study load, ECTS

How to apply?

Short description

This course equips PhD students with the knowledge and skills to leverage Generative AI for their scientific research. You’ll learn how these powerful AI models work, explore the art of prompt engineering, and discover practical tools to accelerate your research process.

Full description

Module 1: Demystifying Generative AI

  • Introduction to Generative AI and Large Language Models (LLMs)
  • Understanding how LLMs work: Unveiling the black box
  • Applications of Generative AI in scientific research (e.g., hypothesis generation, literature review)
  • Ethical considerations, risks and limitations of AI for research
  • Live demonstration: Using LLMs for text generation

Module 2: Mastering Prompt Engineering

  • The art of crafting effective prompts: Guiding the AI towards your research goals
  • Strategies for prompt design and optimization
  • Hands-on practice: Using Generative AI tools for your specific research needs. Designing prompts and using AI tools to craft research papers and literature reviews.

Learning outcomes

  • Explain the basic principles of Generative AI and LLMs
  • Craft effective prompts to leverage Generative AI for scientific research
  • Utilize practical AI tools to enhance your research workflow and productivity

Course requirements

  • Basic understanding of AI and machine learning concepts
  • Familiarity with using software tools and online platforms
  • English Language

Places available

10

Planned educational activities and teaching methods:

  • A blend of theory and practice: lectures followed by hands-on exercises using real-world research scenarios.
  • Interactive learning: Group discussions and Q&A sessions to encourage active participation.
  • Participants are encouraged to bring a laptop and open an account from any LLM (ChatGPT, perplexity, Gemini, LLama2…) for the hands-on exercises.
  • Participants are encouraged to bring specific research problems or datasets to the course for practical sessions.

Language

  • English

Assessment method

  • other
Prompts challenge

Final certification

Transcript of records

Modality

  • Hybrid

Learning management System in use

Microsoft Teams

Contact hours per week for the student:

4

Specific regular weekly teaching day/time

Time zone

  • CET (Spain, France, Germany, Hungary, Netherlands, Norway)
How to apply?