AI-301
DACA Planet-Scale Distributed AI Agents
Master planet-scale distributed AI agents using Kubernetes, Dapr Workflows, and A2A protocols. Develop expertise in voice-enabled agents, self-hosted LLMs, and fine-tuning LLMs for global-scale applications.
Available Sections:
Details
This advanced course focuses on the design and deployment of planet-scale, distributed AI agents within Data-Augmented, and DACA frameworks. Students will gain expertise in Kubernetes application development, agent-to-agent (A2A) communication protocols, voice-enabled agents, and distributed agent systems using Dapr Workflows and Agents. The course also covers self-hosting large language models (LLMs) and fine-tuning LLMs for specialized applications. Through hands-on projects, students will build and deploy scalable, distributed AI systems capable of operating at a global scale.
Key Learning Modules
Module 1Certified Kubernetes Application Developer (CKAD)
Master advanced Kubernetes concepts for AI application development. Deploy and manage AI workloads on Kubernetes, preparing for CKAD certification through practical exercises.
Module 2Dapr Agents and Workflows with MCP and A2A
Build distributed AI agents using Dapr Workflows and Agents. Integrate Dapr with MCP and A2A protocols to enable secure, context-aware communication and coordination in planet-scale AI systems.
Module 3Voice-Enabled AI Agents
Develop and integrate voice-enabled AI agents. Learn the fundamentals of voice interfaces, testing, and optimization for enhanced agent performance.
Module 4Self-Hosted Large Language Models (LLMs)
Set up and manage self-hosted large language models. Ensure scalability and performance for LLM infrastructure in distributed AI environments.
Module 5Fine-Tuning Large Language Models
Master techniques for fine-tuning large language models for specific use cases. Evaluate and deploy fine-tuned LLMs in production environments.
Course Outcomes
Develop and deploy Kubernetes-based AI applications in preparation for Certified Kubernetes Application Developer (CKAD) certification.
Integrate Dapr, MCP, and A2A communication protocols for distributed AI systems.
Design and deploy voice-enabled AI agents.
Build distributed AI agents using Dapr Workflows and Agents.
Host and manage self-hosted large language models (LLMs).
Fine-tune LLMs for domain-specific AI applications.
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.