Introduction to Developing AI Agents

Übersicht

AI agents are set to become a key driver in the evolution of artificial intelligence in the near term. AI agents are revolutionizing generative AI by leveraging LLMs as reasoning engines and using tools (function calls) to perform multistep tasks.

In this course, Introduction to Developing AI Agents, you’ll learn to create these AI agents. First, you’ll explore the fundamentals of AI agents, including their architecture, types, and use cases.

Next, you’ll implement a basic AI agent framework in Python. Finally, you’ll learn to develop advanced agents that leverage LLMs to reason, interact with its environment, and achieve goals.

By the end of this course, you’ll have the skills to build agentic AI Applications (with memory and tool-using capabilities) to automate workflows.

Lehrplan

• Course Introduction
Overview of AI agents
Importance of AI agents in modern AI systems
Course objectives and outcomes
• Fundamentals of AI Agents
Definition and characteristics
Types of AI agents (reactive, deliberative, interactive)
Key components: Perception, Decision-Making, and Action
Use cases and applications
• AI Agent Architecture
Understanding agent environments
Key architectural components (sensors, effectors, reasoning engines)
Introduction to tools and function calls for task execution
• Implementing Basic AI Agents
Setting up the development environment
Building a simple AI agent in Python
Testing agent functionality
• Introduction to Large Language Models (LLMs) in AI Agents
Overview of LLMs and their capabilities
Leveraging LLMs for reasoning tasks
Integrating LLMs into basic agent framework
• Advanced AI Agent Development
Designing agents with memory capabilities
Building tool-using agents
Case study: Multi-step task automation with AI agents
• Developing Agentic AI Applications
Understanding environmental interaction
Strategies for achieving complex goals
Real-world examples and applications
• Course Project
Developing a functional AI agent with memory and tool-use features
Applying AI agent to automate a simple workflow
• Conclusion and Next Steps
Recap of key learnings
Future trends in AI agent development
Additional resources and continued learning opportunities

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Unterrichtet von

Muhammad Sajid

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Fachgebiete

Computer Science