Intro to AI Agents with Python
A practical guide to understanding, building, and evaluating AI agents using Python for task automation and problem-solving.
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Fundamentals of AI Agents
Unit 1: Defining AI Agents and Their Characteristics
What is an AI Agent?
Autonomy Explained
Reactivity in AI Agents
Pro-activeness Defined
Social Ability of Agents
Unit 2: Types of AI Agents and Python Structure
Simple Reflex Agents
Model-Based Agents
Goal-Based Agents
Utility-Based Agents
Agent Code Structure
AI Agent Architecture: Perception, Reasoning, and Action
Unit 1: Understanding Agent Architecture
Agent Core Components
The Agent's Inner Loop
Environments Demystified
Sensors and Actuators
Agent Architectures
Unit 2: Implementing Agent Components
Data Ingestion
Rule-Based Systems
Action Execution
Putting It All Together
Debugging Agents
Building Basic AI Agent Behaviors with Python
Unit 1: Reflex and Model-Based Agents
Hello, Reflex Agent!
Reflex Agent: Task 1
State of Affairs
Model-Based in Python
Model-Based: Task 1
Unit 2: Goal and Utility-Based Agents
Goal-Oriented Agents
Goal-Based in Python
Maximizing Happiness
Utility-Based in Python
Putting It All Together
Designing and Evaluating AI Agents for Problem-Solving
Unit 1: Designing and Implementing Your AI Agent
Problem Definition
Agent Design Choices
Coding the Agent
Testing Your Agent
Optimization Strategies
Unit 2: Evaluating and Improving Your AI Agent
Defining Metrics
Performance Evaluation
Areas for Improvement
Ethical AI
Deployment Checklist