Join our webinar to explore the powerful MLOps capabilities within Snowflake’s Data Cloud.
Discover how Snowflake streamlines the end-to-end machine learning lifecycle starting from data preparation and model training to deployment, including monitoring and observability for production workloads.
During the webinar we are going to take a look at advancement in MLOps in Snowflake that make everyday life of Data Scientists, ML Analysts and Analytics Team Leaders much easier and as a consequence lead to gaining competitive advantage of your organisations in terms of AI adoption.
Learn how Snowflake’s MLOps capabilities enable teams to:
- Simplify Data Access and Preparation: Leverage Snowflake’s secure, governed, and scalable data platform to access clean, curated data for training and inference — with no data movement required.
- Build and Train Models with Flexibility: Integrate seamlessly with leading ML frameworks and tools such as Python, scikit-learn, MLFlow, and more, using Snowpark and external functions.
- Deploy Models with Confidence: Discover how to register, version, and deploy models directly within Snowflake, ensuring reproducibility and governance at scale.
- Monitor and Manage ML Pipelines: Learn about best practices for tracking performance, monitoring drift, and automating model retraining using native features of Snowflake MLOps.
- Collaborate Across Teams: Enable data scientists, data engineers and business users to work together more efficiently by centralizing data and ML workflows in a single platform.
Speakers

Jakub Mackowiak
Data Architect
Software Mind
Register Here