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Join us for a FREE hands-on Meetup webinar on Introduction to Agentic AI | Friday, March 21st, 2025 · 7:30 PM IST/ 10:00 AM EDT Join us for a FREE hands-on Meetup webinar on Introduction to Agentic AI | Friday, March 21st, 2025 · 7:30 PM IST/ 10:00 AM EDT

AI Agents & Agentic AI – Building Intelligent Autonomous Systems

Harnessing Agentic AI to Automate, Optimize, and Scale AI-Driven Workflows

Duration

4 Days (8 hours per day)

Level

Intermediate Level Level

Design and Tailor this course

As per your team needs

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The rise of AI Agents and Agentic AI is transforming the way businesses automate workflows, interact with data, and enhance decision-making. This course is designed to provide a deep dive into AI agents, covering the fundamental concepts, architectures, and real-world applications.

Participants will learn how to design, implement, and optimize AI-driven agents capable of executing tasks autonomously using LLMs, reinforcement learning, multi-agent collaboration, and tool integration. The course includes hands-on coding exercises, case studies, and best practices to help professionals build scalable, production-ready AI Agents.

By the end of the course, participants will have a strong foundation in AI Agents, enabling them to create intelligent, context-aware, and goal-driven systems that can operate with minimal human intervention.

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Introduction to AI Agents & Agentic AI

What are AI Agents?
Difference between traditional AI and Agentic AI
The evolution of AI-driven autonomous systems
Use cases and real-world applications
Key components of an AI Agent

Understanding AI Agent Architectures

Reactive vs. Proactive Agents
Rule-Based Agents vs. LLM-Powered Agents
Single-Agent vs. Multi-Agent Systems
Integrating AI Agents with APIs & External Tools
Ethics and safety in AI Agent design

Building AI Agents Using Large Language Models (LLMs)

Role of LLMs in AI Agents
Introduction to LangChain & OpenAI API
Fine-tuning LLMs for Agent-based systems
Memory and Context Management in AI Agents
Hands-on: Creating an AI Chatbot with Memory

Multi-Agent Collaboration & Autonomous Decision-Making

Understanding Multi-Agent Systems (MAS)
Communication & coordination between AI Agents
Reinforcement Learning (RL) for AI Agent optimization
Task Delegation & Prioritization
Hands-on: Building a Multi-Agent System for Workflow Automation

AI Agents with Tool Use & API Integration

How AI Agents interact with tools
Tool-Use API & Function Calling in OpenAI GPT Models
Connecting AI Agents with external systems (databases, APIs, automation tools)
Hands-on: Implementing an AI Agent that interacts with APIs

Building Autonomous AI Workflows

Automating complex tasks with AI Agents
Integrating AI Agents with Cloud & Enterprise Systems
Real-world applications in finance, healthcare, and business process automation
Hands-on: Developing an end-to-end AI-powered automation workflow

Deploying AI Agents in Production

Scaling AI Agents for enterprise use
Deploying AI Agents on AWS, GCP, or Azure
Optimizing performance & minimizing errors
Best practices for maintaining AI Agents in production
Hands-on: Deploying a cloud-based AI Agent

Future of Agentic AI & Next Steps

Latest advancements in Agentic AI
Next-generation AI Agents & self-improving models
Emerging frameworks & tools
How to continue learning and growing in AI Agent development

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