Interpreting analysis results Decision-making frameworks Creating actionable recommendations Implementation planning

Group EDA exercise Visualization workshop Analysis interpretation Project presentations

Descriptive statistics Correlation analysis Trend analysis Basic inferential statistics

Basic chart types and their uses Visualization best practices Tool overview (Excel, Power BI, Tableau) Creating effective visualizations

Purpose and importance of EDA Statistical summary techniques Pattern recognition Outlier detection

Hands-on cleaning workshop Common cleaning scenarios Tool demonstrations Project review and feedback

Excel for data cleaning Introduction to Python/SQL for data preparation Data cleaning best practices

Normalization techniques Aggregation methods Feature engineering basics Data formatting and standardization