Case Studies and Life Sciences Applications

This course adopts a comprehensive approach to building digital solutions within a corporate setting in the life sciences. Attendees will gain a broad overview of the data science pipeline - including machine learning and agentic AI - while also exploring advanced topics and drawing inspiration from real-world life sciences application case studies. The programme spans three full-day sessions.

Day 1
The first day focuses on the advancements data science can bring to life science applications. We will examine specific challenges and corresponding solutions relevant to the life sciences, and discuss concrete use cases of machine learning and agentic AI. Throughout the day, participants will work directly on small projects and gain insights from presentations by industry practitioners.
Responsible lecturer: Thomas Ott

Day 2
The second day delves into advanced topics in machine learning operations (MLOps).
Machine Learning Operations
Defining best practices for data, code, and models has become a key component in transforming organizations into data-driven enterprises. In this introductory session, participants will learn the fundamentals of MLOps and understand its significance in modern digital environments.
Main lecturer: Nitin Kumar

Day 3
The third day focuses on the importance of digital ethics.
Digital Ethics by Design
This session explores how to ensure that digital transformations and technologies are ethical and trustworthy. Participants will gain an overview of current challenges in digital ethics and learn strategies for integrating ethical considerations into the design of digital solutions.
Main lecturer: Deepak Bansal

This module is part of the CAS in Digital Life Sciences continuing education programme. More information here: CAS in Digital Life Sciences