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🤖LLM EngineerAdvanced

AI Agent Developer Path

Specialize in building autonomous AI agents that can reason, plan, and execute complex tasks. Master frameworks like LangChain, LangGraph, CrewAI, and AutoGen to build sophisticated multi-agent systems.

10 weeks
9 milestones
0 items

Skills You Will Gain

ReAct PatternLangChainLangGraphCrewAIAutoGenTool UseMulti-Agent SystemsAgent MemoryAgent Evaluation

Prerequisites

  • →Python proficiency
  • →Basic LLM/API experience
  • →Understanding of prompt engineering
  • →Familiarity with async programming

Learning Milestones

1

Agent Fundamentals

Understand the theory and patterns behind AI agents.

~12h•0 items

Learning Objectives

  • ✓Understand what makes an AI agent
  • ✓Learn ReAct (Reasoning + Acting) pattern
  • ✓Study different agent architectures
  • ✓Understand agent memory types
  • ✓Learn about tool use and function calling
  • ✓Compare agent frameworks landscape
Content coming soon
2

LangChain Agents

Build agents using the LangChain framework.

Content Summary

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Concepts
0
Papers
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Lectures
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Problems
~15h
•
0 items

Learning Objectives

  • ✓Create basic agents with LangChain
  • ✓Implement custom tools and toolkits
  • ✓Use different agent types (OpenAI, ReAct, etc.)
  • ✓Handle agent memory and context
  • ✓Build conversational agents
  • ✓Debug and trace agent execution
Content coming soon
3

LangGraph for Complex Workflows

Build stateful, cyclical agent workflows with LangGraph.

~18h•0 items

Learning Objectives

  • ✓Understand graph-based agent design
  • ✓Build stateful agent workflows
  • ✓Implement conditional branching
  • ✓Handle cycles and loops in agents
  • ✓Build human-in-the-loop patterns
  • ✓Create persistent agent state
Content coming soon
4

Advanced Tool Design

Design and implement sophisticated tools for agents.

~15h•0 items

Learning Objectives

  • ✓Design effective tool APIs
  • ✓Build tools with proper error handling
  • ✓Create tools that return structured data
  • ✓Implement tool authentication
  • ✓Build tools that call other APIs
  • ✓Create tool documentation for agents
Content coming soon
5

Multi-Agent Systems with CrewAI

Build role-based multi-agent systems with CrewAI.

~15h•0 items

Learning Objectives

  • ✓Design agent roles and responsibilities
  • ✓Build agent crews for complex tasks
  • ✓Implement task delegation patterns
  • ✓Handle agent collaboration
  • ✓Build hierarchical agent systems
  • ✓Optimize crew performance
Content coming soon
6

AutoGen & Conversation-First Agents

Build multi-agent conversation systems with AutoGen.

~15h•0 items

Learning Objectives

  • ✓Understand AutoGen architecture
  • ✓Build conversational agent groups
  • ✓Implement human-in-the-loop patterns
  • ✓Handle agent disagreements
  • ✓Build code-writing agent teams
  • ✓Integrate with external tools
Content coming soon
7

Agent Memory & Context Management

Implement sophisticated memory systems for agents.

~12h•0 items

Learning Objectives

  • ✓Design short-term and long-term memory
  • ✓Implement vector-based memory retrieval
  • ✓Build conversation summarization
  • ✓Handle context window limitations
  • ✓Create persistent agent knowledge bases
  • ✓Implement memory compression techniques
Content coming soon
8

Agent Safety & Guardrails

Implement safety measures and guardrails for agents.

~12h•0 items

Learning Objectives

  • ✓Design agent safety boundaries
  • ✓Implement action validation
  • ✓Build approval workflows for risky actions
  • ✓Handle agent failures gracefully
  • ✓Implement cost controls
  • ✓Create audit trails for agent actions
Content coming soon
9

Agent Evaluation & Optimization

Measure and improve agent performance.

~12h•0 items

Learning Objectives

  • ✓Design agent evaluation benchmarks
  • ✓Measure task completion rates
  • ✓Evaluate tool selection accuracy
  • ✓Optimize agent prompts
  • ✓Reduce agent latency and costs
  • ✓A/B test agent configurations
Content coming soon