# Practical Data Science

> Interview preparation, end-to-end projects, and applied workflows across CV, NLP, ML, SQL, and time series.

![Status: complete](https://img.shields.io/badge/status-complete-brightgreen)

Open [`28-practical-data-science.ipynb`](./28-practical-data-science.ipynb) for learning objectives, prerequisites, and recommended reading order.

## Topics Covered

- Data science interview prep: statistics, ML, SQL, and coding
- End-to-end project workflows with real datasets
- Applied tracks: computer vision, NLP, recommender systems, causal ML
- MLOps and statistics for production data scientists

## Prerequisites

Phases 00–16 complete.

## What Comes Next

[29-ai-hardware-llm-validation/README.md](../29-ai-hardware-llm-validation/README.md)
