Advanced AI Agents

Production AI Agents with Python

The complete engineering guide to building AI agents that actually work in production. From tool calling and LangGraph state machines to multi-agent orchestration, vector memory, streaming APIs, and Kubernetes deployment. Covers the 2025–2026 ecosystem: MCP, Pydantic AI, E2B code execution, browser agents, and enterprise guardrails.

30 Modules
4.4h Duration
Text + Code Format
Free Cost
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Prerequisites
  • Python proficiency (async/await, type hints, dataclasses)
  • Basic LLM API experience (OpenAI or Anthropic)
  • Familiarity with REST APIs and Docker basics

What you'll learn

  • Understand the 2025–2026 agent ecosystem and pick the right framework for each use case
  • Build type-safe tools with Pydantic and wire them to OpenAI, Anthropic, and Gemini APIs
  • Design stateful agent workflows with LangGraph nodes, edges, and conditional routing
  • Implement short-term and long-term memory using vector stores and RAG pipelines
  • Orchestrate multi-agent systems with supervisor patterns and parallel execution
  • Instrument agents with LangSmith tracing, cost dashboards, and automated evals
  • Deploy production agents as FastAPI services in Docker on cloud infrastructure
  • Harden agents against prompt injection, runaway loops, and adversarial inputs

Course Curriculum

30 modules · 4.4 hours total

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