3.0 Agentic AI Specialisation with AgentOps Bootcamp

Why It Matters

Enterprise adoption of agentic AI is accelerating, and the talent pool with practical, end‑to‑end deployment skills remains limited; this bootcamp directly bridges that gap, enabling companies to operationalize multi‑agent workflows faster.

Key Takeaways

• 5‑month bootcamp covers 12 leading agentic AI frameworks
• Learners build production‑grade multi‑agent solutions on AWS, GCP, Azure
• Curriculum includes MCP and A2A protocols, AgentOps lifecycle tools
• Four capstone projects deliver end‑to‑end deployments across cloud and local stacks
• Graduates receive portfolio ready for enterprise AI roles

Pulse Analysis

The surge in generative AI has evolved into a new frontier: agentic AI, where autonomous agents collaborate to solve complex tasks. Companies across finance, healthcare, and logistics are piloting multi‑agent workflows to automate decision‑making, yet they struggle to find talent that can move beyond prototypes to production. Specialized training programs like Krish Naik’s bootcamp address this shortage by offering a structured, hands‑on pathway that mirrors real‑world enterprise requirements, positioning graduates as immediate contributors to AI‑driven initiatives.

The bootcamp’s curriculum is notable for its breadth and depth. Participants engage with a suite of twelve frameworks—LangChain, LangGraph, OpenAI Agents SDK, Google ADK, AWS Strands, CrewAI, LlamaIndex, Claude Code, AutoGen, n8n, and LangFlow—ensuring familiarity with the tools shaping the agentic AI ecosystem. Critical to 2026’s standards, the program teaches the two foundational communication protocols, MCP and A2A, alongside advanced concepts such as Agentic Retrieval‑Augmented Generation (RAG), context engineering, and agent security. Integration with the AgentOps lifecycle, using SDKs and observability platforms like LangSmith, Opik, and Langfuse, equips learners to monitor, debug, and iterate on live agents at scale.

From a career perspective, the bootcamp delivers tangible outcomes. The four capstone projects span the major cloud providers—AWS, GCP, Azure—and a fully local stack, each built on distinct architectures and deployment strategies. This portfolio demonstrates a candidate’s ability to deliver end‑to‑end, production‑ready solutions, a credential that differentiates them in a competitive job market. For enterprises, hiring graduates means accessing a ready‑made talent pool capable of accelerating agentic AI adoption, reducing time‑to‑value, and maintaining a strategic edge in the rapidly evolving AI landscape.

Original Description

Enrollment links: https://www.krishnaik.in/liveclass2/AgenticAi?id=11

Agentic AI & GenAI with Cloud 3.0 is the modern, production-focused path to mastering Agentic AI, taking you from core concepts to enterprise-scale multi-agent deployment.

Over 5 months, you'll build with every framework shaping the field today: LangChain, LangGraph, OpenAI Agents SDK, Google ADK, AWS Strands, CrewAI, LlamaIndex, Claude Code, AutoGen, n8n, and LangFlow. You'll master the two foundational protocols of 2026, MCP and A2A, along with advanced Agentic RAG, Context Engineering, Agent Security, and the full AgentOps lifecycle using AgentOps SDK, LangSmith, Opik, and Langfuse.

The course culminates in four end-to-end portfolio projects across AWS, GCP, Azure, and a fully local stack, each built on a distinct framework, architecture, and deployment strategy. By the end, you won't just understand Agentic AI. You'll have shipped it in production.

📞 Have questions or need guidance?

Reach out to Krish Naik's counselling team:

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