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Data Science with Python: Exploratory Techniques to Statistical Insights

Dive into the world of data-driven decision-making. This course will teach you how to leverage Exploratory Data Analysis to unveil market trends and inform strategic choices.

Axel Sirota - Pluralsight course - Data Science with Python: Exploratory Techniques to Statistical Insights
by Axel Sirota

What you'll learn

In a rapidly evolving tech market, understanding customer preferences and market trends is crucial for retailers like Globomantics to stay ahead. In this course, Data Science with Python: Exploratory Techniques to Statistical Insights, you’ll gain the ability to analyze complex datasets and draw meaningful insights for business strategy. First, you’ll explore the fundamentals of Exploratory Data Analysis (EDA), learning how to identify key patterns and anomalies in data. Next, you’ll discover the importance of centrality measures such as mean and median in understanding customer behavior. Finally, you’ll learn how to utilize spread measures like range, variance, and standard deviation to assess market variability and risk. When you’re finished with this course, you’ll have the skills and knowledge of data analysis needed to transform raw data into actionable business strategies.

Table of contents

About the author

Axel Sirota - Pluralsight course - Data Science with Python: Exploratory Techniques to Statistical Insights
Axel Sirota

Axel Sirota has a Masters degree in Mathematics with a deep interest in Deep Learning and Machine Learning Operations. After researching in Probability, Statistics and Machine Learning optimization, he is currently working at JAMPP as a Machine Learning Research Engineer leveraging customer data for making accurate predictions at Real Time Bidding.

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