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Big Data Analytics

Course Reviews

Track :

Programming

Lessons no : 12

For Free Certificate After Complete The Course

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What will you learn in this course?
  • Master techniques for processing and analyzing large-scale structured, semi-structured, and unstructured big data using advanced analytics tools and methods
  • Apply data mining, machine learning, and statistical analysis to extract actionable insights from diverse big data sources
  • Design scalable data architectures and pipelines for efficient big data storage, processing, and management
  • Utilize popular big data analytics platforms like Hadoop, Spark, and Kafka for real-time and batch data processing
  • Interpret complex data visualizations and reports to support strategic decision-making in business and technology contexts
  • Implement data cleaning, transformation, and feature engineering techniques to improve analytics accuracy and efficiency
  • Evaluate big data security, privacy, and ethical considerations in analytics projects and compliance standards
  • Develop predictive models and algorithms to forecast trends and optimize operations using big data analytics

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 | 12

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5
5 Reviews
Shreya Rai P R 

good
2025-10-24

Kavya B R 

nice
2025-05-12

Kushal D 

Good
2025-05-12

Monesh 

GOOD
2025-05-11

K V Ramya 

Good
2025-05-11

M.Mahesh 

good explanation with proper examples
2024-08-01

Danny Macharia 

verry nice and instructional
2024-07-25

Kaycee Grace Ponce Colobong 

INFORMATIVE
2024-07-09

Talila 

good
2024-06-18

Teresa Leviste 

The course was very informative and well- structured with engaging lectures and helpful support.
2024-05-26

Shivang Kashyap 

Great
2023-10-05

Ade Pirmansah 

good
2023-08-25

Show More Reviews

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Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes.