Course description

( to analyze and investigate data sets and summarize their main characteristics, often employing data visualization methods)

What will i learn?

• Data Exploration: Learn how to delve into raw data to uncover patterns, trends, and anomalies.   Data Cleaning and Preprocessing: Master techniques for handling missing values, outliers, and inconsistencies in data.   Data Visualization: Gain proficiency in creating various types of visualizations (histograms, scatter plots, box plots, etc.) to represent data effectively. Statistical Summary: Understand how to calculate and interpret descriptive statistics (mean, median, mode, standard deviation, correlation, etc.) to summarize data characteristics.   Data Distribution: Learn about different data distributions (normal, skewed, bimodal, etc.) and their implications for analysis.

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