DevOps for Data Science: Training & Coaching

You create models, algorithms, and analyses that generate valuable insights – but moving from proof of concept to production is still a challenge? That’s where DevOps for Data Scientists makes the difference: it bridges data-driven insights with best practices from software engineering and IT operations, ensuring models are stable, reproducible, and scalable.

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We empower you with essential DevOps practices – from integrating your work into automated pipelines to applying version control for data and models, and leveraging cloud and container technologies to their full potential. The result: higher productivity, greater reproducibility, and scalable machine learning and analytics projects.

What You’ll Learn in Our ‘DevOps for Data Science’ Training

Fundamentals of Git & Azure DevOps

Efficient Collaboration

Azure Pipelines & CI/CD

Target Audience: The “DevOps for Data Science” training is designed for data scientists, machine learning engineers, and analysts who want not only to develop their models but also to deploy them efficiently, reproducibly, and at scale into production environments.

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Course Length: One day

We are happy to adapt the course content and duration to your prior knowledge and specific requirements. There is also the option to learn DevOps-for-Data-Science practices through personalized coaching. This can be tailored to your needs – for example, in the form of code reviews, pair programming, or the joint development of best practices (e.g., for CI/CD pipelines).