AI Agents for DevOps

Your AI Agent Journey

Transform from DevOps engineer to AI agent architect in 8 weeks

AI Foundations

AI/ML fundamentals for infrastructure teams

AI Stack

Build modern AI infrastructure

AI Agents

Design autonomous agent systems

Production

Deploy agents at scale

Course Curriculum

6 comprehensive modules with hands-on labs

🧠

AI/ML Fundamentals

Week 1 • 6 hours

AI vs ML vs LLMs (infrastructure lens)
Model types & infrastructure needs
Training vs Inference patterns
Model serving: API vs Self-hosted
Lab: First Model Inference API

🏗️

AI Infrastructure Stack

Week 2 • 6 hours

Modern AI infrastructure layers
Vector databases & object storage
CPU vs GPU workload patterns
Model registries & versioning
Lab: Vector DB with pgvector

📚

AI Terminology & Concepts

Week 3 • 6 hours

Tokens, embeddings & context windows
Prompt engineering basics
RAG vs Fine-tuning architectures
Multi-agent vs single-agent systems
Lab: Vector Similarity Search

🤖

Understanding AI Agents

Week 4 • 6 hours

What are AI agents? (DevOps view)
Tool usage, memory & reasoning
Agents vs traditional automation
Cost-benefit analysis framework
Lab: Building Your First Agent

🎯

Agent Categories

Week 5 • 6 hours

Reactive vs Planning agents
Tool-using agent patterns
Multi-agent collaboration (Crews)
Infrastructure implications
Lab: Different Agent Types

🔌

Protocols & Communication

Week 6 • 6 hours

Model Context Protocol (MCP)
REST APIs vs WebSocket patterns
Message queues for coordination
Event-driven architectures
Lab: MCP Server Implementation

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Limited seats - Transform your DevOps career with AI agents

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