Data science

Collecting Data From databases, APIs, web scraping, sensors, etc. Cleaning & Preparing Data Fixing errors, handling missing values, converting formats. Exploring & Analyzing Data Using statistics and visualizations to understand patterns and relationships. Modeling & Machine Learning Applying algorithms to make predictions or discover patterns (e.g., classification, regression, clustering). Communicating Insights Using dashboards, reports, and storytelling to share results with stakeholders.

Predicting customer behavior Fraud detection in banking Disease diagnosis in healthcare Recommender systems (Netflix, Amazon) Optimizing business operations.

Business & Marketing Customer segmentation: Grouping customers based on behavior. Personalized marketing: Recommending products based on past purchases (e.g., Amazon, Netflix). Sales forecasting: Predicting future sales using historical data.