AI Agents 101: Build from Scratch with No Hassle!

By the end of this lecture, you will:

-Understand the fundamental working principles of AI agents.

- Learn how AI agents perceive, process, and act on information.

- Explore different types of AI agents and their real-world applications.

Learning Objectives:

-Identify and differentiate types of AI agents.

-Understand their functionality and use cases.

Key Topics:

Types of AI Agents:

1) Reactive Agents: Respond directly to stimuli (e.g., simple chatbots).

2) Model-Based Agents: Use internal models to predict and act.

3) Goal-Based Agents: Focus on achieving specific objectives.

4) Utility-Based Agents: Optimize decisions for maximum benefit.

? Learning Objectives:

- Identify and differentiate between AI agents and AI models.
- Understand their functionality and real-world applications.

What is an AI Agent? - A system that perceives its environment, makes decisions, and takes actions.

What is an AI Model? - A trained mathematical representation that processes data and makes predictions.

Key Differences: Understanding how agents use models but go beyond prediction to take actions.

By the end of this lesson, you will have a clear understanding of the distinctions between AI agents and AI models and how they work together in AI applications. ?

? Learning Objectives:

- Understand the core building blocks of an AI agent.
- Learn how each component contributes to intelligent decision-making.
- Explore real-world examples of AI agents in action.

Lecture Overview:

AI agents operate through a structured framework that enables them to perceive, process, and act efficiently. In this lecture, we will break down the essential components that make AI agents work:

Perception Module: Gathers data from the environment using sensors or inputs.
Knowledge Base: Stores relevant information to guide decision-making.
Reasoning & Decision-Making Engine: Processes data, applies logic, and determines actions.
Learning Mechanism: Improves performance over time using AI models.
Action Mechanism (Actuators): Executes decisions by interacting with the environment.

What is Microsoft Copilot Studio?

Microsoft Copilot Studio is a low-code AI tool that allows users to build, automate, and extend AI agents with Power Automate and Microsoft 365 data.

Key Features

- Graphical, low-code interface – No coding skills required
- Prebuilt & custom plugins – Connect to multiple data sources
- Automation & orchestration – Create intelligent workflows

What is an AI Agent?

An AI agent is an intelligent assistant that:
Engages in complex conversations
Automates decisions and actions
Connects to knowledge sources & APIs

Use Cases for AI Agents

Sales & Support – Resolve customer queries
HR & Benefits – Employee assistance
Public Health Tracking – Critical data updates
Internal Help Desk – Answer common business questions

With Copilot Studio, anyone—no coding required—can build AI-powered agents to streamline workflows and enhance productivity.