Data Science is the broad field of extracting insight and value from data; Machine Learning is a subset focused specifically on algorithms that learn patterns to make predictions. Every ML engineer uses data science skills, but not every data scientist specializes in ML engineering.
| Factor | Data Science | Machine Learning |
|---|---|---|
| Scope | Broad (data → decisions) | Narrow (predictive algorithms) |
| Typical tasks | EDA, visualization, modeling, storytelling | Model building, tuning, deployment |
| Key tools | Python, SQL, Power BI, ML | Scikit-learn, TensorFlow, PyTorch |
| Role | Data Scientist | ML Engineer |
Learn Data Science first for the broad foundation; specialize into Machine Learning engineering if you enjoy building and deploying models.
Yes — ML is one component of data science, alongside statistics, data engineering and visualization.