Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Subscribe
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
Building AI Agents for Automation
Rating: 4.6 out of 5(8 ratings)
225 students

Building AI Agents for Automation

Get a brief overview of AI Agents with an example to build a Voice AI Agent
Created byStudyopedia Trainings
Last updated 1/2026
English

What you'll learn

  • Learn AI Agents from scratch.
  • Get a quick overview about AI Agents
  • Build a Voice AI Agent from scratch
  • Learn about Agentic AI
  • Create an AI Agent

Course content

2 sections • 9 lectures • 54m total length

  • About Course0:49

    Explore the fundamentals of AI agents, their components, architecture, and types, compare them with Agentic AI, and learn to design a voice AI healthcare assistant with practical use cases.

  • AI Agents – Overview and Components2:15

    this course introduces ai agents as autonomous systems that plan and adapt with a large language model as their brain, detailing four components: planning, memory, tools, and learning and reflection.

  • AI Agents vs Agentic AI - Differences3:27

    Explore the differences between AI agents and agentic AI, focusing on autonomy, scope, task complexity, proactiveness, learning, governance, and safety of complex, multi-agent workflows.

  • Types of AI Agents2:06

    Learn the four AI agent types—simple reflex, model-based reflex, goal-based, and utility-based—along with practical examples like thermostats, vacuum robots, and navigation systems.

  • AI Agents - Architecture5:04

    Explore the architecture of ai agents and their components, including perception, foundation model, planning, memory, action, and external integration, to perceive, reason, plan, and act autonomously.

  • Advantages of AI Agents2:21

    Explore the advantages of AI agents, including enhanced efficiency, data-driven decisions, 24/7 personalized customer interactions, and high scalability for coordinating complex workflows across systems.

  • Disadvantages of AI Agents2:36

    Explore the disadvantages of AI agents: unpredictable behavior and lack of human touch. Address ethical and security concerns, data privacy, algorithm bias, and the need for governance and oversight.

  • AI Agents – Use Cases6:03

    Explore how ai agents transform industries with autonomous customer service, sales development, clinical scribe tasks, fraud analysis, supply chain disruption prediction, personalized learning, automated research, marketing campaigns, and workflow orchestration.

Requirements

  • A computer with an Internet connection

Description

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.


**Course Lessons**

Section A: Introduction to AI Agents

1. AI Agents – Overview and Components

2. AI Agents - Architecture

3. AI Agents vs Agentic AI

4. Types of AI Agents

5. Advantages of AI Agents

6. Disadvantages of AI Agents

7. AI Agents – Use Cases

Section B: MCP Live Running Example

8. Build a Voice AI Agent

Who this course is for:

  • Those who want to learn AI Agent and how to use it
  • Those who want to learn AI Agents
  • 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

Report abuse