A Deep Dive Into Agentic Systems, Robotics, And AI Design
Master Modern Python programming with static typing and develop robust n8n workflows for Agentic AI. Learn to orchestrate plan-act-observe agent loops with tool calling, memory management, and guardrails. Gain skills in Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and deployment (self-hosted or cloud). Prepares for L1:P1-N8N and L1:P2-FMP certifications.
Master core principles and practices of Agentic AI development preparing you for L1:P3-OOP, L1:P4-FAI and L2:P1-PAI certifications. You will understand foundational theories underlying intelligent agent behaviour and develop hands-on experience to develop context-aware AI agents using the OpenAI Agents SDK to design and deploy functional multi-agent systems.
Advance Agentic AI concepts building on AI-201, with focus on Model Context Protocol (MCP), Agentic Memory, and Agentic RAG. Study established agentic design patterns for building effective agents.
Focus on Agentic Web theory and practical implementation of Agent-to-Agent (A2A) Protocol systems. Explore intelligent agents' interactions in web-based environments, contextual information sharing, and collaboration on distributed tasks. Examine core design principles for web-native, cooperative AI systems and how A2A protocols enable real-time communication in diverse environments.
Focus on cloud-first development methodologies for Agentic AI systems. Explore scalable, distributed AI architectures using Docker and Kubernetes for deploying AI Agents and MCP Servers. Design and deploy production-ready AI applications optimized for cloud environments through hands-on projects.
Cover enterprise-grade distributed application runtime environments with focus on Distributed Application Runtime (Dapr) implementation, managed database systems, and messaging architectures. Design and implement planet-scale AI agent networks for global distributed infrastructure.
Explore Physical AI and humanoid robotics, focusing on integration of ROS 2, Gazebo Robot Simulator, and NVIDIA Isaac™ AI robot development platform. Learn to design, simulate, and deploy advanced humanoid robots capable of natural interactions, covering ROS 2 for robotic control, simulations with Gazebo and Unity, and using OpenAI’s GPT models for conversational AI.
Master Ray for distributed AI computing, optimizing scalable machine learning, data processing, and model serving in cloud-based AI pipelines.
PIAIC Certified Agentic AI & Robotics Engineer Exams