Cloud & Platform Engineers
AI for cloud architecture, cost optimization, and scaling
Viewing the Cloud & Platform Engineers track. 15 tracks available for different roles.
Course Overview
Week 1:
. .
9:00 - 9:15 | Welcome & Orientation
- • Welcome & instructor introductions
- • Course overview & objectives
- • Logistics (breaks, lunch, bathrooms, WiFi)
- • Hybrid format expectations
- • In-person: Participation guidelines
- • Virtual: Camera on/off policy, chat usage
- • Icebreaker: Quick poll
- • What's your primary cloud platform? (AWS / Azure / GCP / Multi-cloud)
- • AI experience level (1-10)
- • One thing you wish AI could automate in your workflow
9:15 - 9:45 | What is AI?
- • What is AI, really? (demystified)
- • AI is not magic (it's pattern matching at massive scale)
- • AI vs ML vs LLM (hierarchy)
- • Three types of AI (overview)
- • Predictive
- • Generative
- • Agentic
- • Common misconceptions debunked
- • When AI helps vs. when it doesn't
9:45 - 10:15 | Predictive AI Deep Dive
- • Predictive AI explained (weather forecasting analogy)
- • How it works (simplified - no math!)
- • Real-world examples:
- • Netflix recommendations
- • Spam detection
- • Traffic predictions
- • **For YOUR work:**
- • Cloud cost forecasting and budget anomaly detection
- • Resource utilization prediction and right-sizing recommendations
- • Deployment failure prediction from CI/CD pipeline metrics
- • Security threat detection in cloud access patterns
10:15 - 10:45 | Generative AI Deep Dive
- • Generative AI explained (creative AI)
- • How LLMs work (simplified)
- • Training on massive text
- • Pattern recognition
- • Next-word prediction
- • Real-world examples:
- • ChatGPT
- • GitHub Copilot
- • AI writing assistants
10:45 - 11:00 | Setup Verification & Break Prep
Break: 11:00 AM - 11:30 AM
11:30 - 11:40 | Lab 1 Introduction
- • Lab 1 overview: "Your First AI Conversation"
- • Learning objectives:
- • Chat with AI model
- • Generate Terraform from natural language
- • Get architecture review feedback
- • Recognize hallucinations in cloud contexts
- • Demo: Instructor walkthrough (5 min)
- • Q&A (3 min)
- • Get started!
11:40 - 12:10 | Lab 1: Your First AI Conversation
12:10 - 12:25 | Lab 1 Debrief & Discussion
12:25 - 12:55 | Agentic AI & Introduction to Agents
- • Agentic AI explained
- • Chatbot (passive) vs Agent (active)
- • Example: Dashboard that shows metrics vs auto-scaling system that responds to them
- • Components of an agent:
- • Goal
- • Reasoning
- • Tools
- • Action
- • Result
- • Modern tooling: MCP (Model Context Protocol) for standardized tool integration
12:55 - 1:20 | Prompt Engineering Workshop
1:20 - 1:30 | Week 1 Wrap-Up & Homework
- • Recap: What we learned today
- • Three types of AI
- • How to use Generative AI for cloud operations
- • Prompt engineering for IaC and architecture
- • Preview: Next Saturday (tease exciting content)
- • Build RAG system with YOUR cloud docs (Terraform modules, ADRs, runbooks)
- • Create your first cloud health monitoring agent
- • AI cost modeling for platform engineering
Between Weeks: Practice & Exploration
Homework
Hands-on exercises to reinforce learning and prepare for Week 2
Support
Office hours, Slack channel, and async help from instructors
Resources
Additional reading materials and video tutorials
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