AI and Data Services

Analyse and design data services involving AI models with respect to business needs, regulations and safety matters.

Flyer presenting the summer school

Students from Data Science and Computer Science

The AI & Data Services Summer School in Lausanne includes morning sessions focused on understanding business needs and technical concepts, featuring invited speakers from various companies and institutions. The afternoons are dedicated to thematic workshops where participants will work in groups on the presented business cases. On Friday afternoon, the week culminates with the presentation of group results to the companies. Here is a day-by-day example of the program:

• Day 1 - Monday

  • Theme of the day: Business case understanding
  • Learning objectives:
    • Understand how to analyse business needs for data services involving AI models.
    • Learn about project management (PM) and customer management (CM) in the context of AI projects.
    • Gain insights from invited speakers from companies regarding business applications of AI and data services.
    • Understand the business cases that will be the focus of the thematic workshops.

• Day 2 - Tuesday

  • Theme of the day: Data engineering
  • Learning objectives:
    • Learn industry practices about data engineering including handling missing data, advanced encoding, anonymisation/pseudonymisation techniques
    • Gain insights from invited speakers from companies related to data engineering practices.
    • Participate to the afternoon workshop on data engineering with the respective business cases.

• Day 3 - Wednesday

  • Theme of the day: Data analysis and AI model creation
  • Learning objectives:
    • Explore advanced concepts such as Explainable AI (XAI), reinforcement learning, LLM configuration and fine tuning.
    • Gain insights from invited speakers from companies active on data analysis and AI model creation.
    • Participate in the afternoon workshop focused on data analysis and AI model creation for the chosen use cases.

• Day 4 - Thursday

  • Theme of the day: MLOPS and deployment
  • Learning objectives:
    • Understand advanced topics on MLOPS and deployment such as sustainable scalability in AI systems, continuous model re-training etc.
    • Gain insights from invited speakers having deployed MLOPS and deployment strategies.
    • Participate in the afternoon workshop on MLOPS and deployment relevant to the specific use cases.
    • Begin working on the final presentation of the group's results.

• Day 5 - Friday

  • Theme of the day: Law, safety and ethics
  • Learning objectives:
    • Analyse legal, safety, and ethical aspects related to AI.
    • Gain insights from invited speakers from companies and public organisations on these crucial topics.
    • Continue working on the final presentation.
    • Present the results of the group work to the enterprises, potentially in the form of a poster or PowerPoint presentation.