This advanced-level course introduces you to Agentic AI — a powerful new approach where AI systems can plan, decide, and act independently to solve complex problems.

You will learn how to design and build autonomous AI agents that can perform tasks such as content generation, decision-making, data analysis, customer support, and workflow automation.

Course Synopsis :

                               The Agentic AI Program is a live, structured training that teaches how modern AI systems are designed to plan, decide, and execute tasks autonomously. Students learn prompt engineering, agent workflows, automation, and integration with real tools to build practical AI solutions. The course focuses on understanding how intelligent systems work rather than just using AI tools. By the end, learners can design and implement real-world AI agents and workflows.

Course Learning Objectives :

Module Details

Module 1 - Foundations of Agentic AI

Understanding how modern intelligent systems actually work

What you will understand
This module builds the mental model of agent-based AI. Instead of seeing AI as a chatbot, you will understand how intelligent systems interpret goals, make decisions, and execute actions step-by-step.

What you will do

• Break down real AI applications into workflows

• Define goals and tasks for an agent

• Map decision flow of an AI system

• Set up the working environment

Tools used
ChatGPT interface, workflow diagrams, system prompts

Outcome
After this module you can explain how autonomous AI systems operate and think in workflows instead of prompts.

Module 2 - Prompt Engineering & Control

Controlling AI behavior instead of guessing responses

What you will understand
You will learn how prompts act as instructions that shape reasoning, reliability, and output structure. The focus is on predictable and repeatable results.

What you will do

• Write structured prompts

• Guide reasoning step-by-step

• Prevent incorrect outputs

• Create reusable prompt templates

Tools used
ChatGPT, structured prompting patterns

Outcome
After this module you can reliably control AI outputs for consistent results.

Module 3 - Agent Architecture

Designing systems that plan and execute tasks

What you will understand
This module explains how agents are internally structured using planners, memory, tools, and execution logic. You will move from single responses to multi-step systems.

What you will do

• Design an agent workflow

• Define tasks and actions

• Simulate multi-step decision making

• Build mini agent systems

Tools used
ChatGPT, workflow logic concepts

Outcome
After this module you can design a working agent workflow instead of isolated prompts.

Module 4 - Knowledge & Retrieval Systems (RAG Concepts)

Teaching AI to use real information instead of guessing

What you will understand
You will learn why AI sometimes produces incorrect information and how modern systems solve this using external knowledge and retrieval methods.

What you will do

• Prepare information sources

• Connect agent to external data

• Reduce hallucinations

• Build a knowledge-based assistant

Tools used
ChatGPT, retrieval workflow concepts, structured context handling

Outcome
After this module you can create AI assistants that answer using real data.

Module 5 - Tools & API Integration

Making AI interact with the real world

What you will understand
AI becomes powerful when it can use tools. This module focuses on connecting agents with external services and actions.

What you will do

• Understand APIs & webhooks

• Connect agent with services

• Trigger external actions

• Handle errors and responses

Tools used
Postman, APIs, webhooks

Outcome
After this module you can connect AI with real services and automate tasks.

Module 6 - Automation Workflows (n8n)

Turning AI into automated systems

What you will understand
You will learn how automation platforms allow agents to perform real operations across multiple applications and steps.

What you will do

• Build workflows in n8n

• Connect AI with automation

• Create multi-step task execution

• Run end-to-end processes

Tools used
n8n, automation workflows

Outcome
After this module you can build AI automation systems instead of manual processes.

Module 7 - Evaluation & Optimization

Making systems reliable and production-ready

What you will understand
This module focuses on improving reliability, measuring performance, and refining agent behavior.

What you will do

• Test outputs systematically

• Improve prompts iteratively

• Debug workflow failures

• Optimize responses

Tools used
Testing methods, structured evaluation

Outcome
After this module you can refine and stabilize AI systems for real use.

Module 8 - Final Project & Deployment

Building a complete real-world agent

What you will understand
You will combine all learned concepts into a functional system.

What you will do

• Design a complete AI workflow

• Integrate tools and automation

• Build and demonstrate project

• Present solution

Tools used
Full stack from previous modules

Outcome
After this module you will have a complete working AI agent project for portfolio use.