Internship← Data Science learning pathData Science · Module 1 of 10
What is data science?
Data science extracts insights and predictions from data.
📖 Key ideas
- Data science combines statistics, programming and domain knowledge.
- Lifecycle: question → data → clean → explore → model → communicate.
- Uses: recommendations, forecasting, fraud detection, healthcare, sports.
- Core tools: Python, pandas, scikit-learn, SQL, Jupyter.
- Roles: data analyst, data scientist, ML engineer, data engineer.
💡 Real-life example: A data scientist is a detective and fortune teller: explains what happened and predicts what's next.
Data scienceExtracting value from data
Domain knowledgeUnderstanding the business area
JupyterInteractive notebook tool
LifecycleSteps of a data project