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“Grow Your ML Garden on Google Cloud” is a hands-on workshop that invites attendees to delve into the world of Machine Learning Operations (MLOps) using Google Cloud Platform (GCP) as a fertile ground for AI development. This workshop will guide participants through the lifecycle of ML projects – from preparing the initial data soil to nurturing and cultivating robust ML models. Emphasizing on MLOps practices, this workshop covers three key areas: preparing the data in a BigQuery’s feature store, developing ML models with Vertex AI, and managing a sustainable MLOps environment using Vertex AI Pipelines. The participants will have the opportunity to predict outages of wind turbines using a real world dataset with time series data.


  • Introduce data and ML capabilities of Google Cloud
  • Illustrate core MLops principles with an industry use-case
  • Offer hands-on experience with state-of-the-art data tools like BigQuery and Vertex AI
  • Give each participant the opportunity to build and deploy their own model


13:30 – 13:45 Planning the Garden: MLOps on GCP
  • Introduction to MLOps and its significance in ML projects
  • Presentation of one case study from the industry
  • Overview of GCP as an enabling environment for ML
13:45 – 14:15 Preparing the Soil: Feature Store on BigQuery
  • The role of Feature Store in ML: Storing and managing data effectively
  • Hands-on activity: Setting up and using a Feature Store in BigQuery
14:15 – 15:00 Cultivar Selection: Running experiments with Vertex AI
  • Exploring the capabilities of Vertex AI for model development
  • Hands-on activity: Training and tuning a ML model on Vertex AI
15:00 – 15:30 Break
15:30 – 16:30 Harvesting Results: Production Pipelines with Vertex AI
  • Insights into production deployment of ML projects
  • Hands-on activity: Deploying and monitoring ML workflows on Vertex AI
16:30 – 17:00 MLOps Challenge: A Kahoot Quiz
Interactive quiz session on MLops principles on GCP