# DataFabric-Academy/ms-fabric-data-science

> Hands-on Microsoft Fabric data science course built around FreshMart customer churn prediction, with PySpark, MLflow, medallion architecture labs and Thai study notes.

- Magnitude: 0.0 out of 10 — Quiet
- Stars: 96 total · +0 stars on 2026-09-29 (UTC), ≈ 0 by evening
- Star trust: star growth looks organic
- Category: Learning & lists · Language: Jupyter Notebook · License: MIT · Created: 2026-09-12 · Last push: 2026-09-16
- GitHub: https://github.com/DataFabric-Academy/ms-fabric-data-science · Homepage: https://learn.microsoft.com/training/paths/implement-data-science-machine-learning-fabric/ · Page: https://gitnova.dev/en/r/DataFabric-Academy/ms-fabric-data-science

## Useful for

- Work through the labs to build a churn model in Microsoft Fabric
- Run the local pipeline and pytest tests without a Fabric capacity
- Study Lakehouse, MLflow Model Registry and Power BI Direct Lake on a sample case

## Why it’s here

- The repository is 17 days old and already has 96 stars.

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 3
- Issues and pull requests: 0
- Watchers: 0
- Average over the last week: 0 per day
- Usual pace: 5 per day
- Latest release: v1.0.0 (2026-09-12)

## Stars per day, last 30 days (oldest → newest, today is partial)

2026-10-04 … 2026-11-02: None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None

## Magnitude by day, last 14 days

09-16 4.5, 09-17 0.2, 09-18 0.2, 09-19 0.2, 09-20 0.0, 09-21 0.0, 09-22 0.0, 09-23 0.0, 09-24 0.0, 09-25 0.0, 09-26 0.0, 09-27 0.0, 09-28 0.0, 09-29 0.0

---

Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-09-29 00:16 UTC, updated every 30 minutes.