π Data Engineer / Analyst Path
L100 L200 L300
You work with data β analytics, BI, ETL pipelines β and want to add AI agents to your data workflows for conversational analytics, automated insights, and intelligent data processing.
Recommended Sequence
Phase 1 β AI Fundamentals for Data People
| Order |
Lab |
Title |
Level |
Time |
| 1 |
Lab 004 |
How LLMs Work |
L50 |
~20 min |
| 2 |
Lab 006 |
What is RAG? |
L50 |
~20 min |
| 3 |
Lab 007 |
What are Embeddings? |
L50 |
~15 min |
Phase 2 β Work IQ & Copilot Analytics
| Order |
Lab |
Title |
Level |
Time |
| 4 |
Lab 047 |
Work IQ β Copilot Adoption Analytics |
L200 |
~45 min |
| 5 |
Lab 048 |
Work IQ β Impact Analytics & Power BI |
L300 |
~90 min |
| 6 |
Lab 075 |
Power BI Copilot β Analytics |
L100 |
~45 min |
Phase 3 β Fabric IQ & Data Agents
| Order |
Lab |
Title |
Level |
Time |
| 7 |
Lab 052 |
Fabric IQ β Conversational Data Agent (NLβSQL) |
L200 |
~75 min |
| 8 |
Lab 053 |
Fabric IQ β Batch AI Enrichment |
L300 |
~90 min |
| 9 |
Lab 051 |
Fabric IQ β Real-Time Intelligence |
L300 |
~75 min |
Phase 4 β Advanced RAG & Search
| Order |
Lab |
Title |
Level |
Time |
| 10 |
Lab 068 |
Hybrid Search β Vector + BM25 |
L200 |
~60 min |
| 11 |
Lab 067 |
GraphRAG β Knowledge Graphs |
L300 |
~90 min |
| 12 |
Lab 083 |
Multi-Modal RAG |
L300 |
~90 min |
Total: 12 labs Β· ~11 hours Β· From data fundamentals to AI-powered analytics