Join the AI Toolkit Developer Workshops Across North America

The landscape of artificial intelligence is evolving from experimental Large Language Models to a new phase known as Agentic AI. This shift introduces autonomous software agents that operate on behalf of users, fundamentally transforming business practices and commerce. To navigate this transition, organizations face the challenge of securely building, deploying, and managing these agents at scale.

To address this need, a series of interactive workshops will be held across North America. These sessions are designed to provide practical, hands-on experience rather than traditional lectures. Participants will learn how to enhance their Kubernetes clusters for AI applications and optimize data warehouses for autonomous agents.

Target Audience

The workshops are tailored for Platform and Security Engineers, as well as Data Practitioners.

Platform and Security Engineers

Engineers in these roles will benefit from a toolkit focused on securing and scaling next-gen workloads.

• Prerequisites: Foundational knowledge of Google Kubernetes Engine (GKE) and containerization.
• Key Activities: Learn defense-in-depth strategies, secure inference endpoints, and automate cluster operations using natural language.

Data Practitioners

Data Engineers, Analysts, and Scientists looking to connect traditional analytics with Agentic AI will find relevant training here.

• Prerequisites: Basic SQL skills and some cloud experience; familiarity with Python is helpful but not required.
• Key Activities: Build governed data pipelines, derive insights from unstructured data, and deploy agents that activate dashboards.

Workshop Tracks

Participants can expect to build full-stack agentic applications through two main tracks:

Track 1: GKE + Data

• AI-Augmented Operations: Manage clusters using natural language with Gemini and MCP servers.
• Secure Sandboxing: Safely deploy AI agents in hardware-isolated environments.
• Massive Scale: Utilize GKE for processing large datasets and creating complex knowledge graphs.

Track 2: Data Engineering & Analytics

• Governed Ingestion: Build a unified data layer for actionable insights using Spark and Knowledge Catalog.
• Conversational Analytics: Create a user-friendly interface for data interaction by integrating vector search and multimodal data.
• Graph-Powered Agents: Develop agents that comprehend complex relationships using BigQuery Graph and the Agent Development Kit (ADK).

Important: Participants must bring their own laptops and power cables to engage in the sessions.

Upcoming Workshop Dates

Registration is now open for the following sessions: