The AI-Native Data Engineer
Put LLMs to Work Inside Your Pipelines—Automate the Grind, Own the Insight
Every model you build is only as good as the data feeding it. Learn to weave LLMs directly into your pipelines and turn data engineering's grind into an unfair advantage.
Data engineering is the unglamorous foundation every AI system stands on—and it's ripe for reinvention. This masterclass is a fast, hands-on guide to integrating large language models directly into your data workflows. You'll go far beyond copy-pasting prompts: you'll craft smarter prompts for data tasks, use AI to write, debug, and optimize SQL and Python faster, embed LLMs at the API level inside pipelines for automation and enrichment, clean and transform messy real-world data with AI, and build agentic workflows that capture and scale subject-matter expertise. Everything is illustrated with instantly-familiar SQL and Python use cases, so you can apply it Monday morning. This is the data course the rest of the catalog depends on.
Your Competitive Moat
AI Hyper-Personalizes Your Experience
This isn't a one-size-fits-all course. It's assessed to your gaps, adapted to you, and finished with a custom deliverable you build and own.
Pre-Masterclass Assessment
You begin with an AI-driven assessment that maps what you already know against everything this masterclass covers. We pinpoint your knowledge gaps up front—so your time goes only where it moves the needle.
An AI-Personalized Path
Your results reshape the masterclass around you. The AI aligns the material, examples, and pace to close your specific gaps—so a fixed curriculum becomes a path built for exactly one person: you.
A Custom Deliverable You Own
You don't leave with a certificate—you leave with a real, working artifact built for your goals. In "The AI-Native Data Engineer," that means a deliverable you can ship, show, and build on. Something you made, not just something you watched.
Proven Transformation Results
Real outcomes from students who completed The LLM Sovereignty Stack™ and built their competitive moats
📈 Career Transformation
💰 Business Impact
What You'll Actually Build
Choose Your Path to Mastery
All modalities include the complete LLM Sovereignty Stack™. Choose based on your learning style and goals.
Self-Paced Mastery
- All 7 modules available immediately
- Lifetime access to content and updates
- Community support and code reviews
- Monthly live office hours
7-Week Live Cohort
- Weekly live workshops with Dr. Lee
- Pipeline reviews on your real data
- Direct instructor access
- Graduation certificate
- Alumni network access
Founder's Edition
- One-on-one mentorship with Dr. Lee
- Pipeline architecture for YOUR data stack
- Automation opportunity audit
- 90-day satisfaction guarantee
4-Day Immersive Bootcamp
Executive intensive format. Build an AI pipeline in one week. Live data-cleaning labs.
Course Curriculum
7 transformative steps · 25 hours of hands-on content
Module 1: Introduction to AI Data Engineering
5 lessons · Shu-Ha-Ri cycle
- Why Data Engineering Is Being Reinvented by AI
- Beyond the Coding Assistant: LLMs Inside Pipelines
- The AI-Native Data Stack
- Where AI Helps—and Where It Hurts—in Data Work
- Your AI Data Engineering Roadmap
Module 2: AI and Data Workflows
5 lessons · Shu-Ha-Ri cycle
- Mapping the Modern Data Workflow
- Identifying High-Leverage Automation Points
- API-Level Integration vs Manual Prompting
- Cost and Latency in AI-Augmented Pipelines
- Hands-On: Instrument a Workflow with an LLM
Module 3: Crafting Smarter Prompts for Data
5 lessons · Shu-Ha-Ri cycle
- Prompting for Structured, Reliable Data Output
- Schema-Constrained Generation
- Prompt Patterns for Transformation and Enrichment
- Guarding Against Silent Data Errors
- Hands-On: Build a Prompt Library for Data Tasks
Module 4: AI for SQL and Python
5 lessons · Shu-Ha-Ri cycle
- Generating and Debugging SQL with AI
- Optimizing Queries with LLM Assistance
- Writing and Refactoring Python Data Code Faster
- Verifying AI-Generated Code Before It Ships
- Hands-On: Accelerate a Real SQL/Python Task
Module 5: Integrating AI into Pipelines
5 lessons · Shu-Ha-Ri cycle
- Embedding LLM Calls at the API Level
- Automation, Analysis, and Enrichment in Flight
- Batching, Caching, and Rate Management
- Error Handling for AI Steps in Pipelines
- Hands-On: Add an AI Enrichment Stage to a Pipeline
Module 6: Data Cleaning with AI
5 lessons · Shu-Ha-Ri cycle
- The Never-Ending Chore: Cleaning Messy Data
- AI-Driven Standardization and Deduplication
- Extracting Structure from Unstructured Data
- Validating AI-Cleaned Data
- Hands-On: Clean a Real Messy Dataset with AI
Module 7: Building Agentic Data Workflows
5 lessons · Shu-Ha-Ri cycle
- From Steps to Agents: Autonomous Data Workflows
- Capturing Subject-Matter Expertise in Agents
- Scaling Expert Workflows Across the Team
- Monitoring Agentic Pipelines
- Capstone: Ship an Agentic Data Pipeline
Production-Grade Tech Stack
Master the same tools used by OpenAI, Anthropic, and Google to build frontier AI systems
Frequently Asked Questions
No. That's one small piece. The core of this masterclass is integrating LLMs at the API level inside your pipelines—automating transformation, enrichment, and cleaning, and building agentic workflows that scale expertise. It's engineering, not copy-paste.
Because every model in this catalog is only as good as its data. This masterclass fills the one gap the rest of the catalog assumes away: the pipelines that produce clean, enriched, training-ready data.
Working SQL and Python. If you can write a query and a data script, you're ready. No ML background required.
Stop Renting AI. Start Owning It.
Join 500+ engineers and founders who've gone from API consumers to model builders—building their competitive moats one step at a time.
Command $250K-$400K salaries or save $100K-$500K in annual API costs. Own your model weights. Build defensible technology moats. Become irreplaceable.
Self-paced · Lifetime access · 30-day guarantee
Start Your TransformationThis is not just education. This is technological sovereignty.