Exploratory Data Analysis Courses

Join our free Exploratory Data Analysis courses and learn key statistical and visualization techniques. Boost your data science skills and make informed decisions. Enroll now and earn certificates upon course completion.

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Exploratory Data Analysis Domains
Level
Time to complete
Free Courses in Exploratory Data Analysis
7 Courses Filters
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Basics of Exploratory Data Analysis
4.51 
99.7K+ Learners
1.5 hrs
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Basics of EDA with Python
4.55 
12.3K+ Learners
2 hrs
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Data Visualisation with R
4.51 
6.2K+ Learners
1 hr
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Data Visualization using Python
4.55 
79.2K+ Learners
2.5 hrs
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Multiple Variate Analysis
4.5 
2.1K+ Learners
1 hr
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Outlier Detection
4.44 
1.8K+ Learners
1.5 hrs
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Exploratory Data Analysis Projects
4.51 
1.7K+ Learners
2.5 hrs

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Master Data Science & Machine Learning in Python
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Master Data Analytics in SQL & Excel
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Exploratory Data Analysis Courses with Certificate


Exploratory Data Analysis (EDA) is essential for discovering data patterns and drawing meaningful insights. These free courses from Great Learning Academy covers crucial statistical and visualization techniques. You'll learn how to explore and summarize datasets, detect anomalies, and interpret data trends. The courses are designed for anyone looking to build a strong foundation in data analysis.

Key Highlights of Our Exploratory Data Analysis Courses:

  • Access to comprehensive, hands-on training

  • Practical exercises with real-world datasets

  • Step-by-step guidance on data exploration

  • Free certification upon completion

Skills Covered

  • Core statistical methods

  • Data visualization techniques

  • Pattern recognition and trend analysis

  • Anomaly detection and data summarization

Who Should Take Our Free Exploratory Data Analysis Courses?

  • Beginners interested in data science

  • Professionals looking to enhance their analytical skills

  • Anyone who wants to gain a foundational understanding of data analysis

What Will You Learn in Our Exploratory Data Analysis Courses?

  • How to effectively explore and analyze data

  • Techniques for visualizing data and identifying trends

  • Methods for detecting and handling anomalies

  • Skills to make informed decisions based on data insights