Core Components and Intelligent Architectures
Building AI Agents: Core Components and Intelligent Architectures
What you’ll learn
- Understand the core components of AI agents and their architectures..
- Build agents with sensors, effectors, memory, and decision-making engines..
- Use tools and frameworks like LangChain, CrewAI, and AutoGen to create agents..
- Design, test, and deploy a personalized AI agent as a final project..
Course Content
- Introduction –> 5 lectures • 10min.
- Core Concepts of AI Agents –> 3 lectures • 6min.
- Sensors – Perception Layer –> 3 lectures • 6min.
- Effectors – Action Layer –> 3 lectures • 6min.
- The Decision-Making Engine –> 3 lectures • 6min.
- The Knowledge Base –> 3 lectures • 6min.
- Communication Interface –> 3 lectures • 6min.
- Putting It All Together –> 3 lectures • 7min.
- Build Your First AI Agent with n8n & ChatGPT-5 – Step-by-Step Module –> 16 lectures • 13min.
Requirements
Building AI Agents: Core Components and Intelligent Architectures
Artificial Intelligence agents are no longer futuristic concepts — they are already powering chatbots, virtual assistants, trading bots, autonomous vehicles, and countless business applications. But what makes an AI agent truly effective? How do we design intelligent systems that can perceive, reason, act, and adapt in the real world?
This hands-on course gives you a complete roadmap to understanding and building AI agents from the ground up. You’ll explore the core components of agent architecture — sensors, effectors, decision-making engines, knowledge bases, and communication interfaces — and learn how these pieces fit together into scalable, intelligent systems.
Through step-by-step lessons, you’ll discover:
- The different types of agents (reactive, deliberative, hybrid) and their use cases
- How agents perceive the world through text, images, audio, and APIs
- How effectors enable agents to take meaningful actions in both digital and physical environments
- The role of reasoning, planning, and memory in decision-making
- How to structure a knowledge base with databases, vector stores, and context caching
- Ways agents communicate with humans, systems, and other agents
- Tools and frameworks like LangChain, CrewAI, and AutoGen that accelerate development
- How to add error handling and safety layers to keep agents reliable and trustworthy
By the end of this course, you will not only understand the anatomy of intelligent agents, but also gain the skills to design, extend, and deploy your own personalized AI agent as a final project.
Whether you are a software developer, ML engineer, or AI enthusiast, this course will equip you with the knowledge and practical experience to build the next generation of intelligent AI systems.