– Numpy for numerical computing
– Pandas for data manipulation and analysis
– Reading data from CSV, Excel, databases, APIs

– Handling missing values
– Data transformations
– Feature engineering techniques

– Using Matplotlib and Seaborn
– Creating clear, insightful plots and dashboards
– Storytelling with data

– Descriptive statistics
– Correlation, distributions, hypothesis testing
– Drawing insights from data

– Building simple models (linear regression, classification)
– Using Scikit-learn
– Understanding model evaluation

– Choose a real-world dataset
– Apply all learned techniques: clean, analyze, visualize, and present insights
– Final presentation + certificate award