Agentic Ai Fundamentals: Creating Autonomous Agents

Learn to design, orchestrate, and automate AI agents with Python and Autogen frameworks

What you'll learn

Understand the core principles of Agentic AI

Implement multi-agent communication and orchestration

Manage agent workflows with state management and termination logic

Integrate human-in-the-loop for safer AI decisions

Requirements

Basic Python knowledge (variables, functions, loops)

Familiarity with APIs (making simple requests) is helpful but not mandatory

A computer (Windows/Mac/Linux) with internet access

Description

Step into the future of Artificial Intelligence with Agentic AI Fundamentals. This course teaches you how to design, build, and deploy autonomous AI agents using Python, AutoGen, multimodal models, and modern agent orchestration techniques. From async programming to browser automation with Playwright MCP, you’ll gain the hands-on skills to create scalable AI systems with human-in-the-loop controls, advanced state management, and multi-agent collaboration.Whether you’re a developer, QA engineer, AI enthusiast, or automation architect, this course gives you the tools and practical knowledge to master next-generation AI agent design.Understand the core principles of Agentic AIBuild text and multimodal AI assistants using AutoGenImplement multi-agent communication and orchestrationManage agent workflows with state management and termination logicIntegrate human-in-the-loop for safer AI decisionsExtend AI capabilities with MCP tools and browser automationWho This Course Is ForDevelopers exploring AI agent developmentQA/Test Automation Engineers expanding into AI-powered testingAI enthusiasts wanting to build practical autonomous agentsSolution Architects & Tech Leads adopting multi-agent frameworksCourse ContentModule 1: Foundations of Generative & Agentic AIIntroduction to Generative AIFundamentals of Agentic AIAsync Programming in PythonModule 2: Building Smart AI AgentsCreating a Text AI Assistant using AutoGenDesigning a Multimodal AI AssistantMulti-Agent Collaboration with RoundRobin Group ChatModule 3: Control & Orchestration of AgentsSetting Termination Conditions for AgentsHuman-in-the-Loop InteractionManaging Agent State EffectivelySelectorGroupChat for Intelligent RoutingModule 4: Extending Agents with ToolsAdding MCP Tool in AI AgentsBrowser Automation with Playwright MCP

Overview

Section 1: Intro & Key Characteristics of Agentic AI

Lecture 1 Key Characteristics of Agentic AI

Section 2: Introduction to Generative AI

Lecture 2 GenAI vs Traditional AI

Lecture 3 Core Idea Behind Generative AI

Lecture 4 How GenAI Works

Section 3: AI Agent Browser Automation with Playwright MCP

Lecture 5 Part 1-AI Agent Browser Automation with Playwright MCP

Lecture 6 Part 2-AI Agent Browser Automation with Playwright MCP

Section 4: Basics Of Autogen

Lecture 7 Agentic AI: Async Programming In Python

Lecture 8 Agentic AI: Building a Multimodal Assistant

Lecture 9 Agentic AI: Multi AI Agent with RoundRobin Group Chat

Lecture 10 Agentic AI: Text AI Assistant Using AutoGen

Lecture 11 Agentic AI: Termination Condition

Lecture 12 Agentic AI : Human-in-the-Loop

Lecture 13 Agentic AI : Managing State

Lecture 14 Agentic AI :SelectorGroupChat

Section 5: Adding MCP Tool in AI Agents

Lecture 15 Part1_Adding MCP Tool in AI Agents

Lecture 16 Part2_Adding MCP Tool in AI Agents

Section 6: Code For Students

Lecture 17 Important Installation Links

Lecture 18 Code

Section 7: When AI Agents Become a QA Team: Playwright MCP in Action

Lecture 19 When AI Agents Become a QA Team: Playwright MCP in Action

Developers exploring AI agent development,QA/Test Automation Engineers expanding into AI-powered testing,AI enthusiasts wanting to build practical autonomous agents,Solution Architects & Tech Leads adopting multi-agent frameworks