Database Engineers
AI for query optimization, data management, and automation
Viewing the Database Engineers track. 15 tracks available for different roles.
Course Overview
Week 1: Foundations
. .
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 database platforms do you work with? (PostgreSQL, MySQL, Oracle, SQL Server, MongoDB, etc.)
- • AI experience level (1-10)
- • One AI concern you have about database work
9:15 - 9:45 | What is AI?
- • What is AI, really? (demystified)
- • AI is not magic (it's pattern matching)
- • 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:**
- • Query performance prediction ("this query will take 45 seconds")
- • Storage capacity forecasting
- • Workload anomaly detection (unusual query patterns)
- • Replication lag prediction
- • Connection pool exhaustion early warning
10:15 - 10:45 | Generative AI Deep Dive
- • Generative AI explained (creative AI)
- • How LLMs work (simplified)
- • Training on massive text (including SQL documentation!)
- • 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 - Database Edition"
- • Learning objectives:
- • Chat with AI model about database topics
- • Write effective prompts for query optimization and schema design
- • Understand parameters
- • Recognize hallucinations in database advice
- • 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: Getting a query optimization tip vs having an agent analyze your slow query log automatically
- • 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 database tasks
- • Prompt engineering basics
- • Preview: Next Saturday (tease exciting content)
- • Build a DBA knowledge base with YOUR runbooks
- • Create your first DB health monitoring agent
- • Real query tuning cost analysis
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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