Introduction to Al and Machine Learning on Google Cloud

Overview

About the Webinar

AI is everywhere. Knowing where to start on Google Cloud is the hard part.

Pre-trained APIs, AutoML, custom training, BigQuery ML, Gemini: each one solves a different problem, and choosing the wrong one is where many AI projects stall. This 1-day introductory course gives you the map, then puts you in the labs to use it.

You start with AI and ML fundamentals and the Google Cloud infrastructure that supports AI and ML workloads. From there, you move step by step to Generative AI with Gemini, covering multimodal capabilities, prompt design and model tuning.

Along the way, you will:

🧭 Explore BigQuery ML, AutoML, Agent Platform, Gemini, Model Garden and MLOps
🧪 Build and evaluate ML models through practical, hands-on labs
⚖️ Compare pre-trained APIs, AutoML and custom training, and learn when to use each
🔁 Understand how MLOps automates the ML workflow from start to finish

Every concept is paired with a lab, so you leave with working experience, not just notes.

Walk in curious about AI. Walk out knowing what to build and how.

What you will learn/Key takeaways

• Understand the AI and ML tools, technologies and infrastructure available on Google Cloud
• Build and explore generative AI projects with Gemini, including multimodal capabilities, prompt design and model tuning
• Build and evaluate ML models using BigQuery ML
• Build an ML model end to end using Agent Platform
• Compare pre-trained APIs, AutoML and custom training, and know when to use each
• Understand MLOps and ML workflow automation on Google Cloud