Module week: Week 35 (starting 25 August 2026)
Lecturer: Wei Ouyang (Assistant Professor at KTH; DDLS Fellow)
Live introduction on Zoom — Tuesday 25 August 2026, 10:00–12:00 CEST. Module 1 is delivered live to open the course; the recorded lectures for the following modules are released at the start of each module week (see the schedule).
Lecture slides
The slides from the live introduction are online — they open straight in your browser, no download needed. Move through the deck with the arrow keys, space, the on-screen arrows, or by swiping on a phone. Press F for full screen, and P to print or save the whole deck as a PDF.
Module 1 serves as the foundational introduction to the Data-Driven Life Sciences (DDLS) course. This basic module is designed to familiarize participants with the overarching principles and goals of DDLS, getting prepared for machine learning topics and providing a comprehensive overview of the course structure, content, and logistics. Participants will be introduced to the various topics that will be covered in the subsequent modules, as well as the format of the course, which includes lectures, computer labs, and seminars. The module will also outline the examination and certification requirements.
A key focus of this module will be on introducing tools and tips to facilitate self-learning, including the basics of machine learning, running and using Google Colab, and prompt engineering with AI assistants (e.g. ChatGPT, Claude, Gemini). Participants will learn how to use these tools to enhance their learning experience by digesting course material, understanding new concepts, and assisting with coding tasks in the computer lab.
In addition, the module will guide students in building their first scientific AI agent, giving hands-on experience with an agent that can help retrieve, reason about, and summarize domain-relevant information—laying the groundwork for more advanced agent workflows later in the course.
By the end of this module, attendees will have a solid understanding of what to expect in the course, including the practical and theoretical components, ensuring they are well-prepared for the advanced topics in the following modules.
The computer lab notebook will be released at the start of the module week; you will present your lab work at the Friday seminar.