Generative AI

HRDC Reg. No: 10001677341
Course Duration: 32 Hours (4 Days)

Course Overview

Agentic AI represents the next evolution beyond traditional prompt-based Large Language Model (LLM) systems. Instead of simple input-output interactions, Agentic AI enables intelligent agents to plan, reason, collaborate, use tools, and execute tasks autonomously.

This intensive 4-day hands-on program guides participants from foundational concepts to advanced implementation using both no-code platforms (n8n, Custom GPTs) and code-based frameworks (LangChain, CrewAI).

Participants will also gain deep expertise in the Model Context Protocol (MCP)—learning how to design, build, and deploy MCP servers and clients using Python, and integrate them into enterprise-grade AI systems.

By the end of the course, learners will be equipped to build scalable, interoperable, and production-ready AI agent systems.

Who Should Attend

• Software Developers & Engineers
• AI/ML Practitioners
• Automation Specialists
• Technical Consultants
• Digital Transformation Leaders
• IT Professionals exploring AI integration

Why Choose This Course

• HRDC Claimable Course (HRDC Reg. No: 10001677341)
• Hands-on labs with real-world tools (n8n, LangChain, CrewAI)
• Covers both no-code and full-code AI agent development
• Deep dive into MCP (Model Context Protocol) — an emerging enterprise standard
• Build production-ready AI systems, not just prototypes
• Learn integration with APIs, tools, and enterprise workflows

Learning Outcomes

By the end of this program, participants will be able to:

• Differentiate between traditional LLM systems and Agentic AI
• Design single-agent and multi-agent architectures
• Build automation agents using n8n (no-code)
• Develop intelligent agents using LangChain and CrewAI
• Understand and implement MCP architecture
• Build MCP servers and clients using Python
• Integrate MCP with agent frameworks and LLM systems

Prerequisites

• Basic knowledge of Python (syntax, functions, JSON handling)
• Familiarity with LLMs (e.g., ChatGPT)
• Understanding of prompt engineering fundamentals
• Basic knowledge of APIs and client-server architecture
• (Optional) Exposure to machine learning concepts

Lab Setup

Participants should prepare:

• Laptop with minimum 8GB RAM
• Python environment installed (Python 3.9+)
• Internet access
• Accounts for:
  • n8n
  • OpenAI / ChatGPT
• Code editor (e.g., VS Code)

Teaching Methodology

• Instructor-led interactive sessions
• Step-by-step guided labs
• Real-world case studies
• Hands-on agent development
• Collaborative exercises and mini projects
• Continuous Q&A and troubleshooting