Generative AI

HRDC Reg. No: 10001658404

Course Duration: 40 Hours (5 Days)

Course Overview

Agentic AI represents the next evolution beyond traditional Generative AI, enabling systems to plan, reason, use tools, access enterprise data, and execute multi-step workflows autonomously.

This intensive 5-day program is designed for engineers and technical leaders who want to build production-ready AI agents using Python. Participants will move beyond prompt engineering into designing autonomous, tool-using, memory-enabled, and multi-agent systems integrated with enterprise environments.

The course emphasizes real-world implementation, combining LLMs, orchestration frameworks, RAG architectures, and deployment strategies to prepare participants for modern AI engineering roles.

Who Should Attend

• Software Engineers / Senior Developers
• AI / ML Engineers
• Solution Architects
• Automation & Platform Engineers
• Product & Technical Leads (hands-on)

Why Choose This Course

• Focus on Agentic AI (next-gen AI beyond GenAI)
• Hands-on development using Python + modern AI frameworks
• Covers multi-agent systems, RAG, MCP, and deployment
• Includes real-world enterprise use cases and capstone project
• Prepares participants for AI Agent Engineer / Architect roles

Learning Outcomes

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

• Understand the difference between Agentic AI and traditional GenAI
• Design and build autonomous AI agents using Python
• Implement multi-agent systems with orchestration and coordination
• Integrate LLMs with tools, memory, and reasoning frameworks
• Develop RAG-powered agents for enterprise data
• Apply Model Context Protocol (MCP) concepts
• Evaluate, debug, and optimize AI agents for production
• Deploy scalable Agentic AI systems using best practices

Prerequisites

Technical Requirements

• Python fundamentals (functions, classes, environments)
• Basic knowledge of REST APIs, JSON, and Git
• Introductory understanding of GenAI / LLMs (recommended)

Nice to Have

• Experience with FastAPI or Flask
• Basic cloud knowledge (AWS, Azure, GCP)

Lab Setup

Hardware

• Laptop with minimum 16GB RAM
• Stable internet connection

Software

• Python 3.10+
• VS Code / PyCharm
• Git & GitHub account
• Docker (optional)

Libraries & Tools

• openai, langchain, langgraph, autogen
• pydantic, chromadb, faiss-cpu
• fastapi, uvicorn, tiktoken, pytest

Access Requirements

• OpenAI / Azure OpenAI / Gemini API keys
• Sample enterprise datasets (provided)

Teaching Methodology

• Instructor-led deep technical sessions
• Hands-on labs (70% practical focus)
• Real-world AI agent development scenarios
• Guided implementation of frameworks (LangChain, LangGraph, AutoGen)
• Capstone project with production-ready output
• Debugging, evaluation, and deployment exercises