This workshop is a refined evolution of our earlier AI on the Cloud session — redesigned, polished, and delivered fully on-site! While it builds on the foundations introduced before, it stands completely on its own and is structured for both newcomers and returning participants.

In this hands-on session, we’ll train a neural network in the cloud and turn it into something tangible: a live system that can receive input and respond with real predictions over the internet. Along the way, you’ll see how models move from experimentation to deployment using Google Cloud Platform — not just inside notebooks, but across managed infrastructure.

Expect to work with Vertex AI for remote training, Cloud Storage for artifact management, and virtual machines configured for real inference — all while managing IAM permissions, billing credits, and responsible resource cleanup.

By the end of this workshop, participants will be able to:

• Set up and configure a production-aware ML project on Google Cloud Platform, including IAM roles, billing with provided credits, and required API enablement.

• Train and validate a neural network using Vertex AI notebooks, while managing datasets and storing model artifacts properly in Cloud Storage.

• Export and operationalize trained model weights, preparing them for real-world inference outside the training environment.

• Provision and configure a virtual machine for deployment, automate environment setup, and expose a live inference endpoint accessible over the internet.

Come curious. Leave understanding how AI systems survive outside your laptop.