AI Agent for Absolute Beginners

An AI agent is a system capable of independently carrying out tasks and reaching objectives by creating its own workflows and leveraging available tools, instead of simply reacting to single prompts. It operates using large language models (LLMs) as its core “brain,” allowing it to reason, plan, learn, and make informed decisions.  The AI Agents tutorial is prepared for students, engineers, and professionals. This tutorial will be useful for understanding the AI agent concepts for AI enthusiasts.
Components of AI Agents
An AI agent generally consists of several interconnected modules that enable its advanced functionality:

• Planning Module: Decomposes complex objectives into smaller, actionable steps and organizes them in a logical order.
• Memory Module: Maintains context by storing information across interactions, combining short-term memory (such as recent conversations) with long-term memory (past knowledge and experiences).
• Tool Integration: Interfaces with external tools, APIs, and software to execute tasks like data retrieval, email automation, or database queries.
• Learning and Reflection: Incorporates feedback loops to assess its outputs, learn from errors, and continuously enhance its performance.

1. Who this course is for:

• Those who want to learn about AI Agents
• Those who want to learn about how to use an AI Agent
• Learn about the process of the AI Agents and Agentic AI
• Those who want to understand the process of creating an AI Agent
• Gain a deep understanding of building a Voice AI Agent from scratch
• Learn the difference between AI Agents and Agentic AI

**Course Lessons**

Section A: Introduction to AI Agents

• AI Agents – Overview and Components
• AI Agents vs Agentic AI
• Types of AI Agents
• AI Agents - Architecture
• Advantages of AI Agents
• Disadvantages of AI Agents
• AI Agents – Use Cases

Section B: MCP Live Running Example

• Build a Voice AI Agent