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Statistics and Data Mining for Data Science

Course Reviews

Track :

Programming

Lessons no : 4

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What will you learn in this course?
  • Master statistical analysis techniques for data science, including regression, hypothesis testing, and probability models for large datasets
  • Apply data mining algorithms such as clustering, classification, and association rules to extract actionable insights from complex data
  • Utilize statistical approaches to identify patterns, trends, and anomalies in massive datasets for informed decision-making
  • Implement practical data analysis workflows using statistical tools and data mining software to solve real-world data science problems

How to Get The Certificate

  • You must have an account Register
  • Watch All Lessons
  • Watch at least 50% of Lesson Duration
  • you can follow your course progress From Your Profile
  • You can Register With Any Course For Free
  • The Certificate is free !
Lessons | 4


We Appreciate Your Feedback

Excellent
90 Reviews
Good
95 Reviews
medium
8 Reviews
Acceptable
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Not Good
1 Reviews
4.4
194 Reviews
Sneha Banula 

The course so informative and engaging
2025-12-03

N sarath chandra bose 

BOSE
2025-12-03

Eslam Bosha 

very interesting
2025-11-25

Daniel Tut 

I completed this online course, and I found it very interesting and engaging. The content was organized, easy to follow, and highly relevant to the subject
2025-11-25

Carl Martin Rathgber 

-
2025-11-23

Ayush Koul 

I found the video lectures very helpful and appreciated the practical examples. However, adding more interactive quizzes after each section would help reinforce concepts.
2025-11-22

CHEBOLU SIDDARDHA 

///
2025-11-22

Dhanush Shankar 

Good
2025-11-21

Rohit Singh 

awsome teaching
2025-11-21

Puneethashree. K. P 

It was good
2025-11-20

Krity Kumari 

Very nice
2025-11-20

Okikechukwu Ekpe 

Short but detailed
2025-11-15

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Statistical Analysis and Data Mining addresses the broad area of data analysis, including data mining algorithms, statistical approaches, and practical applications. Topics include problems involving massive and complex datasets .