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EnglishWhat the S2DS Five-Week Programme Involves
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S2DS (Science to Data Science) is a five-week, intensive, project-based data science and AI training programme that has been running since 2014. It is designed for analytical PhDs and MScs who want to move from academia into industry. From day one, participants join a small team working on a real commercial client project, using agile management methods with mentorship from an experienced data scientist, and are expected to deliver something with real impact for the client within those five weeks.
The core structure: a real project, not a classroom course
The programme is built around client work rather than lectures. According to S2DS, participants are "immersed in the day-to-day life of a data scientist" by working with clients in a small team from the first day. Each team is guided by an experienced data scientist mentor and develops deliverables for the client over the five weeks.
This means the learning is driven by the project: you apply the analytical skills from your PhD or MSc to a commercial problem, rather than practising on toy datasets.
What past projects look like
S2DS lists examples of past projects that show the range of work:
| Project area | Example |
|---|---|
| Large Language Models (LLMs) | A proof-of-concept to automate refactoring notebooks into production-ready scripts using LLMs; established a framework for LLM-based automation and surfaced challenges for the partner to build on |
| Generative AI | Used generative AI tools and a fine-tuned MLflow pipeline to predict gender in a journalism corpus |
| Machine Learning | An ML model using eddy current measurements to predict the depth of flaws in heat exchanger tubes, to improve maintenance regimes and reduce downtime and power losses |
| Natural Language Processing (NLP) | Improved classification of food hazard alerts using NLP, combining rule-based matching and transformers with classifiers in an ensemble pipeline |
These examples illustrate the kind of output expected: a working proof-of-concept or model with a clear business use, delivered in weeks rather than months.
What you develop beyond technical skills
S2DS describes the programme as building on the data science skills learned during an analytical PhD or MSc and applying them in a commercial setting. The stated development areas are:
- Technical approach — shaping and delivering an analytical solution to a client problem
- Teamwork and agile management — working in a small team using agile methodologies
- Business acumen and client management — understanding and managing the client relationship
- Career and technical mentorship — guidance from experienced data scientists
The programme also includes social events and a careers seminar intended to help participants begin their industry journey, plus networking with others making the same academic-to-industry transition.
Who it is for and what to expect
S2DS positions itself as Europe's largest data science and AI training programme, aimed at analytical PhDs and MScs moving into data science roles. The intensity is a feature: five weeks of project work that simulates a data science job while teaching technical and interpersonal skills. One Spring 2025 alumnus, Athul Sivan, described the balance between learning and working as well designed to simulate a real data science role.
If you are considering it, the practical questions to check against your own situation are: whether you have the analytical postgraduate background the programme targets, whether you can commit five weeks to an intensive full-time programme, and whether a client-project format suits how you learn. The programme's own materials do not state pricing or entry requirements beyond the PhD/MSc audience, so confirm those directly with S2DS before applying.