AI-202
DACA Cloud-First Agentic AI Development
Advance your Agentic AI expertise with cloud-first DACA development. Master scalable AI architectures using local Kubernetes, Dapr, FastAPI, and managed cloud services. Deploy production-ready AI applications with serverless containers and Model Context Protocols through hands-on projects.
Available Sections:
Details
This advanced course builds on the foundations of AI-201, focusing on cloud-first development for Data-Augmented, Context-Aware (DACA) Agentic AI systems. Students will explore scalable, distributed AI architectures using local Kubernetes, advanced API development, and managed cloud services. The course covers distributed application runtime (Dapr), managed databases and messaging systems, model context protocols, and serverless container deployment. Through hands-on projects, students will design and deploy production-ready AI applications in cloud environments.
Key Learning Modules
Module 1Rancher Desktop with Local Kubernetes
Learn to configure and manage local Kubernetes clusters using Rancher Desktop for AI development. Deploy AI workloads in a Kubernetes environment, mastering the fundamentals of scalable AI architectures.
Module 2Advanced FastAPI with Kubernetes
Develop scalable APIs for Agentic AI systems using advanced FastAPI features. Deploy FastAPI applications on Kubernetes and optimize performance for AI-driven workloads.
Module 3Dapr for Distributed AI Applications
Master the Distributed Application Runtime (Dapr) to build distributed AI applications. Implement workflows, state management, pub/sub messaging, and secrets for scalable and resilient AI systems.
Module 4CockroachDB and RabbitMQ Managed Services
Integrate managed cloud services like CockroachDB and RabbitMQ into AI architectures. Learn to ensure scalability and reliability in distributed AI systems through efficient database and messaging workflows.
Module 5Model Context Protocol (MCP)
Apply Model Context Protocol to enhance AI agent communication. Design and implement context-aware interactions for Agentic AI systems, enabling sophisticated agent coordination.
Module 6Serverless Containers Deployment with Azure Container Apps
Deploy production-ready AI applications using serverless Azure Container Apps. Learn to monitor and scale serverless AI workloads in modern cloud environments.
Course Outcomes
Configure and manage local Kubernetes clusters using Rancher Desktop for AI development.
Develop advanced APIs for Agentic AI systems using FastAPI and Kubernetes.
Implement Dapr workflows, state management, pub/sub messaging, and secrets for distributed AI applications.
Integrate CockroachDB and RabbitMQ managed services into AI architectures.
Apply Model Context Protocol for enhanced AI agent communication.
Deploy serverless containerized AI applications using Azure Container Apps (ACA).
Prerequisites
Note: These prerequisites provide essential knowledge for success in this course. If you haven't completed these courses, consider taking them first or reviewing the relevant materials.