Jan 22, 2027
Feb 5, 2027

ENID | Enabling Innovation with Data Science & AI at ETH Zurich

A 5-day executive program at ETH Zurich for leaders who want to turn data and AI into business value.
9:00h-17:00h
ETH Zurich - "Swiss AI Tower" Andreasturm, Andreasstrasse 5, 8092 Zurich-Oerlikon, Switzerland
Courses & Workshops
Speaker(s):

Presentation

Organizations generate massive amounts of data, yet many struggle to turn it into results. This unique executive program gives decision-makers a practical, strategic framework to identify high-value opportunities, avoid common pitfalls, and lead successful data-driven initiatives.

Why Join

ENID helps leaders navigate fast-changing technologies and rising expectations by focusing on real-world impact. You will learn how to evaluate data and AI opportunities, build trust in analytics, and drive innovation across your organization.

Who Should Attend

Ideal for executives, CDOs, digital and innovation leaders, project owners, and managers responsible for data initiatives and data-driven decisions. No technical or coding knowledge is required.

What You Will Learn

+  Data & AI strategy for leaders: Understand key data science, machine learning and AI concepts and their business implications.

+  Opportunity evaluation: Assess feasibility, risk, cost, and value using proven frameworks.

+  From concept to MVP: Explore how high-impact data products are designed and tested.

+  Responsible & trustworthy AI: Address data quality, ethics, explainability, and governance.

Leading transformation: Measure impact, manage stakeholders, and support adoption.

Your Outcomes

You will leave with practical business knowledge, a clear roadmap for implementing data science projects, tools for leading data-driven change, and a network of peers tackling similar challenges.

Delivered by the Swiss Data Science Center

ENID is taught by experts from the Swiss Data Science Center – a joint initiative of ETH Zurich and EPFL – combining academic discipline with hands-on industry insight. The program was created with the support of EPFL Extension School.

Details

Target audience

Experienced professionals and executives wishing to steer data science initiatives and generate business impact. The course will be given in English.

Dates and schedule

  • Fri. January 22, 2027, 9am to 5pm
  • Thu. January 28, 2027, 9am to 5pm
  • Fri. January 29, 2027, 9am to 5pm
  • Thu. February 4, 2027, 9am to 5pm
  • Fri. February 5, 2027, 9am to 5pm

Instructors

  • Prof. Olivier Verscheure, Executive Director, Swiss Data Science Center (SDSC) - EPFL & ETH Zurich
  • Dr. Silvia Quarteroni, Head of Innovation, SDSC - EPFL & ETH Zurich
  • Dr. Anna Fournier, Principal Data Scientist, SDSC - ETH Zurich
  • Dr. Matthias Galipaud, Senior Data Scientist, SDSC - ETH Zurich
  • Dr. Dan Assouline, Senior Data Scientist, SDSC - EPFL
  • Dr. Saurabh Bhargava, Principal Data Scientist, SDSC - ETH Zurich
  • Arshjot Khehra, Senior Data Scientist, SDSC - ETH Zurich
  • Paulina Körner, Data Scientist, SDSC - ETH Zurich
  • Thibaut Loiseau, Machine Learning Engineer, SDSC - EPFL
  • Kyle van de Langemheen, Machine Learning Engineer, SDSC - EPFL

Program Director

  • Prof. Olivier Verscheure, Executive Director, Swiss Data Science Center (SDSC)  

Certification

An ETH Zurich certificate will be delivered at the end of the course - a minimum attendance of 80% is required.

Course venue

ETH Zurich - "Swiss AI Tower" Andreasturm, Andreasstrasse 5, 8092 Zurich-Oerlikon, Switzerland
Room 16+17 at the 14th floor

Prerequisites

  • Prior experience working with data in a practical context, such as data reporting, visualization, and statistical analysis using structured data, is required.
  • Participants are required to bring their own laptop for use during hands-on practical exercises (installation of KNIME Analytics Platform free software is necessary for hands-on experience.)
  • No coding experience required.

Course fee

4000.- Swiss Francs
General discount: 10% special discount for ETH employees and alumni, as well as SDSC partners.

Registration

Please register by January 15th, 2027, through the ETH Zurich School for Continuing Education website.

Number of participants is limited.

Contact

For any other course-related questions, please contact Dr. Anna Fournier at anna.fournier@sdsc.ethz.ch.

Programme

Day 1: Introduction to data science and digital transformation
  • Data science history, terminology and basic concepts
  • Digital transformation – becoming data-driven
  • Hands-on session with no-code platform (KNIME) – supervised learning
  • AI project management strategies and tools
Day 2: Fundamentals of machine learning (part 1)
  • Strength and limitations of different supervised learning algorithms (including deep learning) and performance metrics, with hands-on session (KNIME)
  • Best practices for industrialisation of solutions and reusability of digital assets
  • Presentation of 3 use cases delivered by SDSC
Day 3: Fundamentals of machine learning (part 2)
  • Strength and limitations of different algorithms for unsupervised learning and time series forecasting, with hands-on session (KNIME)
  • Ethical and legal aspects of AI, with an overview of model explainability and bias mitigation technique
  • Canvassing exercise – how to start a project on the right track
Day 4: Natural language processing (NLP)
  • History of NLP, algorithms and applications, with hands-on session (KNIME and ChatGPT)
  • AB testing for business impact assessment
  • Presentation of 3 use cases delivered by SDSC
Day 5: Computer vision (CV) and generative AI
  • Computer Vision (CV) algorithms and applications, with a hands-on beginner-friendly interactive programming session (in python)
  • Generative AI in NLP, CV and other areas
  • Presentation of 2 use cases delivered by SDSC
  • Group discussion and feedback on canvassed projects by participants

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