Agentic AI is redefining how enterprises operate. The shift from Generative AI to Agentic AI is not
incremental — it is architectural. Organisations that delay building this capability risk competitive
disadvantage as autonomous systems become embedded in core enterprise workflows across Finance,
Operations, Engineering, and Customer Experience. By 2028, 33% of enterprise software applications will include Agentic AI — up from less than 1% in 2024. This full-stack, production-ready capability-building programme transforms engineering talent into Agentic
AI practitioners — from concept to deployment. Participants move beyond LLMs to Large Action Models
that translate AI reasoning into enterprise-grade actions. The 160-hour programme is structured over 12
weeks, blending live instruction, supervised lab time, mentor reviews, and a 40-hour capstone build. Every participant codes across all layers of the full stack — backend agent logic through to frontend UI.
WHO SHOULD ATTEND
- Software Engineers and Full-Stack Developers
- AI/ML practitioners transitioning to Agentic systems
- GCC technical talent targeted for AI-led transformation
- Tech leads designing autonomous workflow solutions
ENTRY PRE-QUISITES
- Familiarity with Generative AI concepts and terminology
- Hands-on Python programming experience
- Exposure to front-end frameworks (React / Angular preferred)
TECHNOLOGY STACK
Python · LangChain · LangGraph · LlamaIndex · CrewAI · FastAPI · Streamlit · Langflow · PydanticAI · OpenAI /LLM APIs · GitHub + CI/CD · LangSmith · Vector DBs
KEY OUTCOMES
- Production-Ready Agentic AI Systems — design, build, and deploy agents that operate reliably in
enterprise environments• - RAG Pipeline Implementation — build retrieval-augmented generation systems with dynamic context retrieval
- Multi-Agent Orchestration Capability — coordinate crews of AI agents across complex business
workflows - Full-Stack AI App Deployment — ship complete applications from backend agent logic to working
frontend UI - Human-in-the-Loop Workflow Design — build governed AI systems with appropriate human oversight
- Enterprise-Grade Code Quality Practices — deliver production code with lint, test, and CI/CD discipline
-
-
Module 1: Navigate the Agentic AI Landscape
-
Module 2: Build AI Agents with No Code
-
Module 3: Python Essentials for Agentic A
-
Module 4: LangChain Essentials
-
Module 5: Build RAG Systems
-
Module 6: Advanced RAG with LlamaIndex
-
Module 7: Agentic AI Systems with LangGraph
-
Module 8: Multi-Agent Systems with CrewAI
-
Module 9: Agent Frontends with Low Code
-
Module 10: Course-End Capstone Project
-
