Master the Art of Data Exploration and Visualization with Python Libraries
What you will learn
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Data Cleaning and Preprocessing β Handling missing values, outliers, and data inconsistencies using Pandas and NumPy.
Data Visualization β Creating insightful visualizations using Matplotlib, Seaborn, and Plotly to understand data distributions and relationships.
Feature Engineering β Extracting meaningful features and transforming raw data for better analysis and model performance.
Statistical Analysis β Understanding descriptive statistics, correlation, and hypothesis testing to draw meaningful insights.
Hands-on EDA with Real-World Datasets β Applying EDA techniques to real-world datasets from domains like finance, healthcare, and environment
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