AI Agents
Build autonomous AI agents. Learn planning, reasoning, tool use, and multi-agent systems.
Prerequisites
Complete Level 6: LLMs
🎯What You'll Learn
- ✓Agent architectures and planning systems
- ✓Tool use and function calling in LLMs
- ✓Reasoning and chain-of-thought prompting
- ✓Multi-agent collaboration and communication
- ✓Agent evaluation and benchmarking
💪Skills You'll Gain
🏆Learning Outcomes
📖Interactive Modules (10)
What are AI Agents?
Introduction to AI agents, autonomous systems that perceive and act in environments.
ReAct Pattern
Learn ReAct (Reasoning + Acting) pattern for agents that reason about their actions.
Tool Use & Function Calling
Master function calling and tool use, enabling LLMs to interact with external APIs.
Memory Systems
Understand agent memory: short-term, long-term, and vector database integration.
Agent Planning Strategies
Learn agent planning strategies: chain-of-thought, tree-of-thought, and decomposition.
Multi-Agent Systems
Explore multi-agent systems, collaboration, and communication between AI agents.
AutoGPT Architecture
Understand AutoGPT architecture, autonomous agents that break down and execute tasks.
LangChain Builder
Build complex AI applications with LangChain framework for agent orchestration.
Retrieval-Augmented Generation
Master Retrieval-Augmented Generation, grounding LLMs with external knowledge.
Agent Evaluation Metrics
Learn agent evaluation metrics, benchmarks, and measuring autonomous system performance.