DEMOD.DE-07 · v1.0

Embeddings →
features → models.
Without the breakage.

7 micro-lessons · ~54 min · Real Docker images

DATA PIPELINE · LIVE FLOW

LAKEHOUSE · 3 LANES · INGEST + TRANSFORM + FEATURES

+47/s

SOURCES

· 4

row

TRANSFORMS

· 8

row

FEATURES

· 12

row

LCDLATEST RUN · 4 m 12 s ago · 14.2K rows

DEROLE TRACK

AI for Data Engineers

Embedding pipelines, hybrid retrieval, eval automation.

WHY THIS MATTERS · SNAP INTERNAL

Top-of-funnel role for data-engineering accounts; 64% of new team plans buy this track first.

WHAT YOU'LL LEARN

01Embedding pipelines

02Vector ops at scale

03Hybrid retrieval

04Eval automation

YOU'LL BE ABLE TO

Run embeddings at lakehouse scale

Tune hybrid retrieval

Automate eval into your CI

RUNNABLE ON YOUR MACHINE

$ docker pull snap/ai-data:lesson-01

$ docker run --rm -it snap/ai-data:lesson-01

snap/ai-data:lesson-01

VERIFIED ENGINEER REVIEWS

Hybrid retrieval lesson moved our recall +12%.

@de_daniVERIFY ON GITHUB

Eval-in-CI is now our gate to merge.

@kofi.infraVERIFY ON TWITTER

LESSONS7

HOURS~0.9

LEARNERS1,340

THIS WEEK+14%