Welcome to this course on Agentic AI, the future of Artificial Intelligence.
Artificial Intelligence is rapidly evolving beyond traditional chatbots. Today's AI Agents can reason, plan, use tools, access information, remember context, and perform tasks autonomously. As organizations increasingly adopt Agentic AI for automation, research, customer support, data analysis, and decision-making, AI Agent Development has become one of the most in-demand skills in the AI industry.

This beginner-friendly course provides a practical introduction to Agentic AI and teaches you how to build intelligent autonomous AI agents using Python and modern AI development techniques.

What You'll Learn:

By the end of this course, you will be able to:

Intro to Agentic AI & What Makes it Different from Large Language Models (LLMs)
AI Agent Building Blocks & Architecture (Goal, Reasoning Engine, Memory, Tools, Action)
Real-World Agentic AI Examples (AI Coding, Travel Planning & Customer Support Agent)
Building an AI Autonomous AI Agent using Python with Hand-on Training from Scratch
Understand how different functions and tools can work together to accomplish a larger goal.
Learn how autonomous workflows can be designed for practical AI applications.
Create &Use Gemini Free API in Google Colab
Implement AI Agent Memory with Python
Implement AI Agent Tools with Python
Implement AI Agent Reasoning with Python
Implement the Main AI Agent Orchestrator (Agent Components in One Place)
Coding resources are provided to get started Immediately
Future of Agentic AI and Course Wrap-Up

Learn Through Real-World Examples:

Throughout the course, we'll look at examples of AI agents, including:
Travel Planning Agents: research flights, hotels, weather, and create itineraries.
Research Assistant Agents: search information, analyze papers, and generate structured summaries.
Coding Agents: generate code, debug problems, test applications, and suggest improvements.
Customer Support Agents: understand customer requests, retrieve information, generate responses, and escalate complex cases.

Build with Python:

This is not just a conceptual course. You'll move from AI agent architecture to actual Python code, seeing how concepts such as reasoning, memory, tools, and actions translate into working components. You'll also build a practical Travel Planning Agent that demonstrates how an LLM can be combined with Python functions and tools to create a multi-step AI workflow.

Why Take This Course?

Unlike many courses that focus only on theory or framework-specific tutorials, this course explains the core concepts behind Agentic AI while providing practical coding examples that you can run directly in Google Colab.

As demand for AI Agent developers continues to grow, learning how to build intelligent autonomous systems is becoming one of the most valuable skills in AI. However, many beginners face a common challenge. Most tutorials either focus heavily on theory or jump directly into complex frameworks without explaining how AI agents actually work. Concepts such as reasoning, memory, tools, planning, retrieval, and multi-agent collaboration can feel overwhelming when learning on your own. That's exactly why I created this course to first understand fundamentals and then build your own AI Agents with Python.

The course is designed to help beginners understand how modern AI applications are built while giving developers, researchers, and AI enthusiasts hands-on experience with real autonomous agent workflows.

Who This Course Is For?

Beginners interested in AI Agents and Agentic AI
Python developers exploring AI automation
Data scientists and AI practitioners
Researchers and students interested in Generative AI
Software engineers building intelligent applications
Anyone looking to learn the next generation of AI technologies

Tools Used in the Course:

Python
Google Colab (free cloud environment)
Gemini API (free tier)

By the End of This Course:

You will understand how AI Agents think, reason, use tools, manage memory, collaborate with other agents, and autonomously complete complex tasks. Most importantly, you will have built working AI Agent and gained practical experience with one of the fastest-growing areas of Artificial Intelligence.

Start your journey into Agentic AI today and learn how to build the intelligent autonomous systems for real-world applications.