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Official Curriculum Brochure
An advanced program for professionals moving beyond writing prompts to building reliable, scalable, production-ready AI systems. It combines advanced prompting, context engineering, RAG, memory, Model Context Protocol (MCP), tool calling, AI agents, evaluation and governance.
Every module combines concept clarity, live demonstration, structured hands-on practice, and role output.
How prompts, context, memory and reasoning work together in modern AI systems; prompt engineering vs. context engineering.
Zero-shot, few-shot, Chain of Thought, Tree of Thought, ReAct, Reflection, Step-Back and Least-to-Most.
Structure, manage, retrieve and optimize context; design system prompts, user context, memory and output constraints.
Build RAG workflows using enterprise knowledge sources.
Short-term, long-term, session memory and context persistence.
Generate JSON, XML, Markdown, tables and API-ready responses; connect AI with APIs and enterprise systems.
Connect AI to enterprise tools using MCP for interoperability.
Design autonomous AI agents and multi-agent workflows using context-aware reasoning.
Test, benchmark and continuously improve prompt and context performance; defend against prompt injection and unsafe outputs.
Build governance, standards and a production-ready AI application combining prompts, RAG, MCP, agents and evaluation.
Discuss schedule, participant capacity, or enterprise dataset customizations with our learning architects.