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AI

AI Agents

Unlock your future in AI enroll now to master AI Agents! Gain hands-on skills building chatbots, smart automations, and multi-agent systems with real-world projects and tools. No advanced experience needed just your passion to lead the AI revolution!
Gav Ridgeway
Devops Expert, Machine Learning Engineer
DevOps Pre-Requisite Course
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What you’ll learn

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Description

Artificial Intelligence is no longer a buzzword—it’s a revolution reshaping industries across the globe. At the heart of this transformation lie AI Agents: autonomous programs capable of making intelligent decisions, automating workflows, and mimicking human-like reasoning. From personal assistants and intelligent customer service bots to complex decision-making systems in finance, healthcare, and logistics AI Agents are becoming essential.

Why You Should Learn AI Agents Today

The global demand for AI specialists is skyrocketing, and professionals skilled in building AI agents are among the most sought-after. Whether you’re aiming to work with LLMs, build autonomous decision systems, or architect multi-agent platforms, this course will give you the competitive edge. With organizations racing to adopt agentic systems for enhanced productivity and innovation, the opportunity for skilled AI engineers and developers has never been greater.

Course Modules

This course is designed to provide a practical and structured journey into building and deploying AI agents. Covering key concepts, hands-on labs, and real-world projects, it takes you from foundational understanding to developing advanced multi-agent systems.

  • Pre-requisites: Get introduced to AI agents, their types, and development principles. Learn key concepts such as embeddings, databases, and frameworks. Explore ethical considerations and gain insights into testing, scaling, and optimizing AI agents.
  • Agent Architecture & Multi-Agent Systems: Understand how AI agents are architected and how they communicate. Learn about multi-agent frameworks, autonomous agent systems, and secure, ethical practices for designing collaborative agent environments.
  • Building AI Agents: Set up your development environment with Jupyter and GitHub. Learn conversational AI basics and apply them in a guided project and lab where you build a simple, interactive chatbot.
  • API Integrations & Tools: Integrate agents with external tools and services. Work with Claude API, Poe, Kubernetes MCP, and Manus AI to give your agents real-time data access and enhanced functionality.
  • Practical Projects: Apply your skills to real-world tasks like building a news aggregator and a resume screener. Use tools like Playwright and FireSearchTool, and reinforce learning through guided labs.
  • Advanced Agents Projects: Develop agents with audio capabilities like speech translation. Complete a hands-on project for language recognition and build a collaborative multi-agent system in the final lab.

Hands-On Labs & Demos

This isn’t just theory. This course provides practical, interactive labs where you’ll build and deploy your own AI agents using real-world tools. You’ll get access to:

  • A dedicated Jupyter-based development environment
  • Git-based code repositories for experimentation
  • Labs on building chatbots, news aggregators, translators, and decision agents
  • Validation environments and tools for testing your solutions

Every concept is reinforced with live demos and step-by-step labs to ensure you gain not just knowledge, but confidence to build production-grade agentic systems.

Who Should Take This Course?

This course is perfect for:

  • AI/ML Engineers wanting to specialize in agentic systems
  • Software Developers looking to expand into AI
  • Tech Leads & Architects aiming to design intelligent automation workflows
  • Data Scientists exploring LLM-integrated pipelines
  • Anyone passionate about AI and the future of intelligent systems

Basic knowledge of Python and APIs will be helpful, but the course is structured to be beginner-friendly.

Ready to Build the Future?

The AI era is here—and agents are leading the charge. Whether you’re upskilling, reskilling, or just starting out, this course is your gateway into a high-impact, future-proof domain. With expert guidance, hands-on labs, and real-world applications, you'll walk away ready to design, develop, and deploy AI Agents that matter.

👉 Enroll now and become an AI Agent developer!

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What our students say

About the instructor

Gav Ridgeway is a self-taught developer with many years of experience in Python, Data Science, Machine Learning, Artificial Intelligence, and Game Development. As a self-taught developer, Gav understands what it takes to learn and teach new and complex topics. He brings this unique perspective to all his courses. His skills encompass various tools & libraries such as: Pandas, NumPy, PyTorch, Linear Regression, NLP, SVM’s and much more.

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Introduction

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Module Content

Course Introduction 02:57
How to Reach Out to KodeKloud and Engage with the Community

Prerequisites

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Module Content

AI Agents – Introduction 09:42
Types of AI Agents 09:44
Types of Agentic Agents and Multi-Agentic Agents 09:34
AI Development – Key Concepts 09:50
Ethical Considerations 07:18
AI Technologies for Agents – Overview 10:29
Testing and Evaluation of AI Agents 11:37

Agent Architecture & Multi-Agent Systems

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Agentic Architecture and Inter-Agent Communication 07:34
Multi-Agent Frameworks and Architecture 14:42
Autonomous Agent Frameworks 13:32
Security and Ethical AI in Multi-Agent Systems 09:53

Building AI Agents

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Development Environment Overview 06:44
Demo: Setting Up Development Environment 17:16
Lab: Setting Up Development Environment
Understanding Conversational AI – Theories and Design 09:14
Demo: Building a Simple Chatbot 11:00
Lab: Building a Simple Chatbot

API Integrations & Tools

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Claude API – Overview 08:00
Demo: How to Use Claude API 09:32
Poe – Overview 08:22
Demo: How to Use Poe 04:29
Kubernetes MCP 08:02
Manus AI – Overview 08:38

Practical Projects

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Task Automation in AI Agents 08:58
Demo: Exploring Computer Tools – Playwright 11:47
Demo: Building a News Aggretor Using WebSearchTool 13:14
Lab: News Aggregator
Understanding Agent Computer Tools 06:06
Understanding FireSearchTool 07:12
Demo: Searching Resumes for Keywords 18:14
Lab: Resume Screener

Advanced Agents Projects

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Audio AI Agent – Speech Translator 06:43
Demo: Automatic Language Recognition and Translation 15:52
Lab: Language Translator
Understanding Multi-Agent Systems 08:58
Demo: Building a Multi-Agent System 17:53
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This course comes with hands-on cloud labs
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