Agentic AI Masterclass: Build Autonomous AI Agents with Tool

What you'll learn
Understand the core concepts of Agentic AI and Autonomous Systems
Master the ReAct Framework (Reasoning + Acting Loop)
Implement Tool Calling and Function Calling with LLMs
Build AI agents with Short-Term and Long-Term Memory
Implement Retrieval Augmented Generation (RAG)
Work with Vector Databases for contextual AI
Design Multi-Agent Systems and orchestration patterns
Architect production-ready AI workflows
Avoid common mistakes in AI agent design
Prepare for advanced AI engineering interviews

Requirements
Knowledge of Basic Python
Basic Knowledge of AI

Description
Stop Building Prompt Bots. Start Building Autonomous AI Systems.

AI is evolving.

Simple prompt engineering is no longer enough.

The future belongs to Agentic AI — AI systems that can

Think

Act

Use tools

Remember context

Make decisions

Execute multi-step workflows

In this comprehensive Agentic AI Masterclass, you will go beyond ChatGPT-style prompts and learn how to build real autonomous AI agents used in enterprise-grade systems.

This course teaches concepts used in real enterprise AI systems — not just demo chatbots.

Why Agentic AI Matters for Your Career

Companies are moving from
Chatbots ➝ AI Assistants ➝ Autonomous Systems

High-paying AI roles now demand understanding of

Tool Calling

Memory Systems

Vector Databases

Agent Orchestration

LLM Architecture Design

If you master this, you are not just an AI user — you become an AI system designer.

By The End of This Course, You Will Be Able To

Design, build and deploy intelligent AI agents that

Perform multi-step reasoning

Call APIs

Retrieve knowledge

Maintain memory

Collaborate with other agents

Solve real-world enterprise problems

What Students Will Learn

Understand the core concepts of Agentic AI and Autonomous Systems

Master the ReAct Framework (Reasoning + Acting Loop)

Implement Tool Calling and Function Calling with LLMs

Build AI agents with Short-Term and Long-Term Memory

Implement Retrieval Augmented Generation (RAG)

Work with Vector Databases for contextual AI

Design Multi-Agent Systems and orchestration patterns

Architect production-ready AI workflows

Avoid common mistakes in AI agent design

Prepare for advanced AI engineering interviews

This course is for

Developers who want to move beyond prompt engineering

AI Engineers building real-world applications

Software Architects exploring AI system design

Data Scientists transitioning into Generative AI

Professionals preparing for AI Engineering roles

Tech enthusiasts who want to understand how autonomous AI works

Who this course is for
Developers who want to move beyond basic prompt engineering and build real AI agents
AI Engineers who want to understand autonomous AI system architecture
Software Architects exploring LLM-based system design
Data Scientists transitioning into Generative AI and Agentic AI
Python developers interested in AI automation and intelligent workflows
ProfeTech enthusiasts who want to understand how modern AI agents actually workssionals preparing for AI Engineer / LLM Engineer interviews