# Practical Data Science

This folder is the transition from studying concepts to performing applied work under interview-style and project-style constraints. It is broad by design, so the main job of this README is to keep the breadth from turning into noise.

## What This Phase Is For

- Consolidating ML, statistics, SQL, forecasting, and applied deep learning
- Practicing end-to-end workflows instead of isolated techniques
- Preparing for interviews, take-homes, and portfolio projects

## Recommended Order

1. [01_START_HERE.ipynb](01_START_HERE.ipynb)
2. [02_INTERVIEW_PREP.ipynb](02_INTERVIEW_PREP.ipynb)
3. Choose one or two tracks below based on your target role

## Subtracks

- `python-data-science/`: data cleaning, EDA, feature work
- `machine-learning/`: pipelines, validation, ensembles, interpretability
- `statistics-mlops/`: experimentation, metrics, monitoring thinking
- `sql-data-engineering/`: data extraction and transformation habits
- `time-series-forecasting/`: forecasting and anomaly detection
- `computer-vision/`: practical CV workflows
- `deep-learning-nlp/`: applied NLP and deep learning practice
- `recommender-causal/`: recommendation and causal framing
- `solutions/`: answer keys or worked examples where available

## How To Use This Folder Well

- Pick a role first, then limit yourself to the most relevant subtracks.
- Prefer one complete project over sampling ten notebooks shallowly.
- Write up your assumptions, metrics, and trade-offs as if someone else will review your work.

## Capstone Ideas

- Churn prediction with a full validation and monitoring plan
- Forecasting dashboard with anomaly alerts
- Recommendation prototype with offline evaluation
- SQL-to-model pipeline with a short stakeholder-facing writeup

## What Comes Next

- Continue to [../09-mlops/README.md](../09-mlops/README.md) if you want to productionize one of these projects.
- Continue to [../16-model-evaluation/README.md](../16-model-evaluation/README.md) if you want stronger reporting and comparison discipline.
- Continue to [../31-ai-powered-dev-tools/README.md](../31-ai-powered-dev-tools/README.md) if you want faster workflows while building portfolio projects.
