Workshop Series Overview
Welcome!
This training program is designed especially for early-career professionals, such as the Helmholtz AI consultants, who bring strong domain expertise to short-term (3–12 month) consulting projects in machine learning applications. Many of you are working in bioinformatics, neuroscience, and related domains, but the skills taught here are broadly relevant across data-intensive research.
The focus of this series is not just on coding, but on learning the software development practices that make research projects easier to collaborate on, maintain, and scale. These practices are critical for professionals like you, who must quickly build reliable solutions in fast-moving projects, while working with diverse collaborators.
Schedule
The series runs across 8 sessions. Each session includes a mixture of concepts, hands-on practice, and applied discussion. Details are still being finalized, but here is the overall plan:
| Session | Date | Description | |
|---|---|---|---|
| Session 1 | October 6th, 2025 | Introduction, Tools and workflows for effective coding in teams using Git and GitHub | |
| Session 2 | TBD | ||
| Session 3 | TBD | ||
| Session 4 | TBD | ||
| Session 5 | TBD | ||
| Session 6 | TBD | ||
| Session 7 | TBD | ||
| Session 8 | TBD |
Structure of Each Session
Each workshop is carefully structured to maximize both learning and application:
Pre-workshop materials
- Participants receive short readings, tutorials, or coding exercises to onboard and review fundamentals.
- A dedicated GitHub Discussions forum provides space for questions and answers before the live session.
Workshop session
- Live, interactive session focused on group problem solving.
- Includes both toy examples (to learn concepts in a safe sandbox) and applied breakouts using real projects contributed by participants.
Follow-up and consulting
- After each session, I am available for one-on-one or small group consulting, helping participants apply the practices to their own consulting projects.
Team reflection and planning
- The Helmholtz AI consulting team meets to reflect on the past session, and to discuss how to steer the direction of the training series for upcoming sessions.
Why This Matters
Building scientific machine learning applications is not only about models and data. For consultants working on short-term projects, the way you build your code matters as much as what it does. By strengthening your skills in collaborative development, testing, reproducibility, and project design, you will:
- Deliver higher quality solutions to collaborators.
- Make your work easier to hand over and sustain after the consulting period ends.
- Build skills that will continue to pay off throughout your career, regardless of domain.
This series is about raising the baseline of scientific software development — so that every project you work on is not just effective in the short term, but also maintainable, scalable, and reproducible in the long run.