Welcome to the definitive masterclass on building production-grade, enterprise AI applications on Google Cloud. Brought to you by KBS CloudTech, this course is meticulously designed and delivered by an elite team with over 17 years of hands-on enterprise experience. We take you far beyond basic tutorials and introductory theory, diving deep into the cutting edge of AI architecture—moving seamlessly from foundational vector mathematics all the way to fully autonomous agentic workflows and decoupled enterprise tool integration.
What You Will Learn
By the end of this masterclass, you will have built, deployed, and mastered four core pillars of modern enterprise AI:
- Semantic Foundations & Vector Math: Master how AI models understand and map unstructured data into high-dimensional space using Google’s flagship text-embedding-005 model. Unpack the underlying mathematics of Cosine Similarity, Euclidean Distance, and Dot Product (MIPS), and optimize performance using NumPy and Scikit-learn.
- Cloud Vector Databases (BigQuery & AlloyDB AI): Learn how to run petabyte-scale in-place semantic searches in BigQuery ML and execute ultra-fast transactional vector workloads in AlloyDB AI. Build and configure optimized approximate nearest neighbor (ANN) indexes, including IVF and Google’s proprietary ScaNN / Tree-AH quantization architecture.
- Autonomous Workflows with the Agent Development Kit (ADK): Build intelligent, goal-oriented AI agents powered by Gemini. Learn state management, secure session handling, persona definition, parameter tuning for deterministic SQL generation, and how to containerize and deploy your agents live to Cloud Run with custom IAM service accounts.
- Enterprise Connectivity Using the Model Context Protocol (MCP): Eliminate custom integration fragmentation by adopting the “USB-C for AI.” Connect your agents to regional MCP servers hosted in the Google Cloud Agent Registry, enabling zero-wrapper tool discovery, centralized auditing, and decoupled architectural governance.






