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Exploratory Data Analysis (EDA)

Exploratory Data Analysis (EDA)

170 ج.م

200 ج.م

The goal of EDA is to understand the data's underlying structure, identify patterns, detect anomalies, and test hypotheses.

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Has discount
Expiry period 5 Months
Made in English
Last updated at Fri Aug 2024
Level
Advanced
Total lectures 4
Total quizzes 0
Total duration 08:00:00 Hours
Total enrolment 1
Number of reviews 0
Avg rating
Short description The goal of EDA is to understand the data's underlying structure, identify patterns, detect anomalies, and test hypotheses.
Outcomes
  • 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.
Requirements
  • advanced level in statistic

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