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Advanced Agentic AI: Practical Enterprise AI Capability Building
An expert-level engineering program for AI professionals and architects building production-grade Agentic AI systems. It covers advanced reasoning, context engineering, Agentic RAG, MCP, Agent-to-Agent (A2A) communication, multi-agent orchestration, AgentOps, evaluation, security, observability and enterprise deployment.
Six capabilities this program builds so you can architect autonomous AI systems in production.
Design advanced Agentic AI architectures for production, enterprise-scale autonomous systems.
Build autonomous reasoning workflows using ReAct, Reflection, Tree of Thoughts and Planner-Executor patterns.
Develop episodic, semantic and long-term memory architectures for autonomous agents.
Design multi-agent orchestration and Agent-to-Agent communication for complex workflows.
Evaluate, secure and deploy agents at scale using AgentOps and observability practices.
Design and deploy distributed, production-grade Agentic AI platforms.
How the program moves you from expert-level concepts to a multi-agent platform you deploy.
Deep dive into Agentic AI architectures and autonomous reasoning.
Design scalable, production-grade autonomous systems.
Build and consume MCP services across enterprise applications and clouds.
Practice complex orchestration and collaborative agent reasoning.
Evaluate, monitor and deploy agents with full observability.
Design, deploy and present a production-grade Agentic AI platform.
Deep dive into Agentic AI architectures and autonomous reasoning.
Design scalable, production-grade autonomous systems.
Build and consume MCP services across enterprise applications and clouds.
Practice complex orchestration and collaborative agent reasoning.
Evaluate, monitor and deploy agents with full observability.
Design, deploy and present a production-grade Agentic AI platform.
The advanced builds you'll complete, pulled directly from the program's engineering curriculum.
Design, build, deploy and present a complete Enterprise Agentic AI Platform featuring advanced reasoning, context engineering, Agentic RAG, MCP, A2A communication, multi-agent orchestration and AgentOps.
The program spans MCP, A2A, Agentic RAG and leading AgentOps tooling rather than any single vendor stack.
OpenAI GPT · Claude · Gemini · Azure OpenAI · Amazon Bedrock
OpenAI Agents SDK · LangGraph · LangChain · AutoGen · CrewAI · LlamaIndex
MCP · A2A · Agentic RAG · Function calling · Context Engineering · Vector DBs · Knowledge Graphs · Memory
LangSmith · OpenTelemetry · AgentOps · Phoenix · MLflow · Langfuse
n8n · Power Automate · Zapier · Make · REST APIs · Enterprise Connectors
A preview of the modules inside the program. See the full breakdown in the detailed curriculum.
Autonomous AI, reasoning systems and production-grade architectures.
Context hierarchy, routing, compression and dynamic context injection.
ReAct, Reflection, Tree of Thoughts, Planner-Executor and graph reasoning.
Episodic, semantic, procedural, long-term and vector memory for autonomous agents.
Hybrid retrieval, semantic search, reranking and knowledge routing.
MCP servers, authentication, tool routing, governance and versioning; enterprise tool orchestration.
Supervisor, Planner-Executor, hierarchical, swarm and router patterns; Agent-to-Agent communication protocols.
OpenAI Agents SDK, LangGraph, AutoGen, CrewAI, LlamaIndex, Semantic Kernel; production design patterns.
Automated evaluation, tracing, logging, telemetry, monitoring, CI/CD and deployment.
Identity, guardrails, Responsible AI; distributed agent platforms; production-grade multi-agent solution.
Understand how AI agents work, tool calling, memory, orchestration, autonomy levels, and high-value business opportunities.
Hands-on workshop to build, test, and deploy multi-step agentic workflows using modern frameworks and enterprise tools.
Customized capability journey for engineering and innovation teams scaling secure agentic automation across enterprise systems.
Every module, topic, activity and practical application, laid out in the detailed curriculum.