Topic
AI Agents
AI agents use an LLM to plan, call tools and act over several steps. Learn agent loops, tool use, memory, multi-agent orchestration and how to make agents reliable in production.
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AI Agents lessons by course
Hands On AI Agent Mastery Course
All 11 lessons on this topic →- Enterprise Agent Architecture – Building Production-Ready AI AgentsFREE
- Secure Tool Integration – Building Production-Grade AI AgentsFREE
- Lesson 1: Secure Agent FoundationsFREE
- Day 4: Production Web Agent with Resilience
- Day 6: Agent Communication Security
- Day 8: Enterprise Chat Agent Architecture
- Day 10: Secure Code Analysis Agent
- Day 12: Agent Learning & Compliance
Practical AI System Architecture: Building Intelligent Systems with LLMs, RAG, and Agent Frameworks
All 11 lessons on this topic →- Day 19 Agentic Principles: Reasoning, Planning, and Self-Correction in Action
- Day 20 Tool Use and Function Calling: Extending Agent Capabilities Beyond Language
- Day 21 Integrating External APIs: Real-World Agent Actions and Orchestration
- Day 22 Agent Memory Systems: Short-Term, Long-Term, and Semantic Recall for Autonomy
- Day 23 Human-in-the-Loop & Moderation: Ensuring Control and Safety in Agentic Systems
- Day 24 Orchestrating Multi-Agent Systems: Hierarchical and Collaborative Patterns
- Day 25 Building Collaborative Agents with LangGraph/AutoGen: Practical Frameworks
- Day 26 Agentic Workflows: Designing Complex Multi-Step and Adaptive Tasks