course | Python & Power BI Masterclass for Advanced Dashboards

Data Preparation and Cleaning 

• Handling missing, inconsistent, and outlier data 
• Data normalization, scaling, and transformation 
• Structuring datasets for analysis and visualization 
• Feature selection and engineering for insights 
• Hands-on exercises with Python and Pandas 

Exploratory Data Analysis (EDA) 

• Visualizing distributions, relationships, and trends 
• Correlation analysis and identifying key variables 
• Outlier detection and anomaly identification 
• Interactive EDA with Plotly and Seaborn 
• Case study: uncovering hidden insights from a dataset 

Data Mining Techniques 

• Clustering (K-Means, Hierarchical) for pattern detection 
• Classification and regression for predictive insights 
• Association rule mining for identifying relationships 
• Dimensionality reduction for complex datasets 

Statistical and Predictive Analytics 

• Hypothesis testing and significance analysis 
• Predictive modeling with Python (scikit-learn) 
• Model evaluation metrics and validation techniques 
• Using insights to guide business decisions 
• Preparing outputs for dashboard visualization 

From Analysis to Actionable Dashboards 

• Translating analytical findings into dashboard KPIs 
• Visualizing predictive and clustering results 
• Combining multiple analysis outputs into one dashboard 
• Interactive storytelling using Python and Power BI