AI in Production: Introduction to MLOps - Training at EPFL


Johan Berdat joined the SDSC in May 2019 as a Senior Machine Learning Engineer in the Innovation team, based in Lausanne.
After completing his M.Sc. in Computer Science at EPFL, he worked for a few years as a consultant in the industry. Specialized in natural language processing (NLP) and computer vision, he loves challenges in document analysis and knowledge extraction.


Clément Lefeebvre joined the SDSC in January 2019 as a Data Scientist with an emphasis on industry-oriented projects in the Innovation team, based in Lausanne.
He holds a Bachelor of Science degree in Physics, acquired in 2016 from the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. Following this, he earned a Master of Science in Computational Science and Engineering in 2018, also from EPFL. Throughout his academic journey, Clément concentrated on leveraging Data Science and Machine Learning techniques to enhance efficiency in industrial processes. Subsequently, he developed a specialized interest in Generative AI, with a particular focus on Natural Language Processing (NLP), especially in the application of Large Language Models for innovation.


Klemen Voncina joined the SDSC in April 2026 as a Machine Learning Engineer in the Innovation team, based in Lausanne.
Klemen holds an MSc in Artificial Intelligence from the University of Groningen. Prior to this, Klemen worked for several years in both consulting roles and startups. He brings a strong engineering-focused perspective, combined with a solid background in machine learning. He particularly enjoys tackling practical challenges, especially those related to infrastructure and application deployment. Outside of work, Klemen enjoys a range of outdoor activities such as climbing and mountaineering, as well as more home-based hobbies like board games, reading, and tea.


Kyle (Hogir) van de Langemheen joined the SDSC in September 2025 as a Machine Learning Engineer in the Innovation team, based in Lausanne.
Kyle holds an MSc in Artificial Intelligence from the University of Groningen. He brings several years of experience applying AI across research and industry.
Outside of his professional interests, Kyle enjoys hiking, reading, cooking, and coffee.


Thibaut holds a B.Sc in Computer Science from HEIG-VD. Before joining the SDSC, he worked in startups where he developped a diverse skill set combining cloud infrastructure, database and application development. Thibaut is very enthusiatic about new technologies and best coding practices and he is looking forward to supporting the team and its projects.


Ivan-Daniel joined the SDSC Innovation team in September 2022, where he works as a Data Scientist. He obtained an MSc in Robotics (2022) from EPFL and holds a BSc in Microengineering (2019), also from EPFL. His main fields of interest are Machine Learning, Computer Vision, and animal locomotion modeling.

Presentation
Building machine learning models is only a fraction of the effort required to deliver value in production. Critical failures occur at the interface between data science and engineering: brittle pipelines, lack of reproducibility, poor monitoring, and unclear ownership. This 1-day workshop introduces the principles and practices of MLOps, focusing on how to operationalize ML systems reliably and efficiently. It covers classical DevOps methodologies and their adaptation to the ML lifecycle, including versioning, testing, deployment, and monitoring. The course emphasizes practical design choices and trade-offs required to move from notebooks to production-grade systems.
Main objectives:
- Understand the core principles of DevOps and their extension to MLOps
- Structure ML projects for reproducibility, versioning, and collaboration
- Design and implement CI/CD pipelines adapted to ML workflows
- Manage the full ML lifecycle, including experiments, models, and deployments
- Monitor production systems, detect model or data drift, and trigger retraining workflows
Topics covered:
DevOps principles and culture – continuous integration, continuous delivery, automation, and infrastructure as code / Version control, testing strategies, and deployment pipelines / From DevOps to MLOps – adapting engineering practices to the ML lifecycle, experiment tracking, model versioning, and governance / Production ML systems – model deployment strategies, monitoring, drift detection, and continuous retraining workflows.
Details
Prerequisites
To make the most of this course, participants should have:
• Intermediate programming skills in Python
• Basic understanding of ML fundamentals and LLM applications
Participants are required to bring their own laptop for hands-on exercises.
Course fee*
1,000.- Swiss Francs
* 10% special discount for contributing members of EPFL Alumni and EPFL VPI partners, SDSC partners, EPFL AI Center and SNAI partners.
Registration deadline
September 24, 2026
Number of participants is limited
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Prof. Olivier Verscheure is the director and founder of the Swiss Data Science Center (SDSC). Olivier also co-leads a joint training program between EPFL and HEC Lausanne, specifically designed for senior executives. Since 2018, Olivier has been a member of the Board of Directors of Lonza, a global leader in the life sciences sector. This company provides products and services to the pharmaceutical, biotechnology, and specialized healthcare industries.Olivier began his career at IBM Research after earning his Ph.D. in computer science from EPFL. He held several research and leadership positions at the IBM T. J. Watson Research Center in New York and co-created and co-directed the IBM Research center in Dublin, Ireland, before joining the EPFL in 2016.


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Olivier joined the SDSC as a data scientist focused on industry collaborations in February 2023. He obtained a MSc in Physics (2017) from EPFL with a minor in Mathematics, and a PhD in Astrophysics (2021) from Aix-Marseille University. Before joining the SDSC, he worked in a small start-up, as a data scientist, on a variety of topics, including data wrangling, natural language processing and time series forecasting.


Clément Lefeebvre joined the SDSC in January 2019 as a Data Scientist with an emphasis on industry-oriented projects in the Innovation team, based in Lausanne.
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Thibaut holds a B.Sc in Computer Science from HEIG-VD. Before joining the SDSC, he worked in startups where he developped a diverse skill set combining cloud infrastructure, database and application development. Thibaut is very enthusiatic about new technologies and best coding practices and he is looking forward to supporting the team and its projects.

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Roberto holds an M.Sc. and a Ph.D. in Particle Physics from the University of Torino, Italy. He has worked for several years in fundamental research as a senior fellow and data scientist at the CERN Experimental Physics division and on a research project supported by the Belgian National Fund for Scientific Research (FNRS). In 2018 he moved to EPFL to work on data mining and Machine Learning techniques for the built environment and renewable energies. He has started and led multiple collaborations with academic and industry partners in the energy domain. Roberto joined the SDSC in September 2021 as a Principal Data Scientist with the mission of accompanying industries, NGOs and international organizations through their data science journey.
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