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Apprenez de nouveaux concepts auprès d'experts du secteur
Acquérez une compréhension de base d'un sujet ou d'un outil
Développez des compétences professionnelles avec des projets pratiques
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Il y a 3 modules dans ce cours
By the end of this course, learners will be able to prepare raw YouTube datasets, apply MapReduce for large-scale processing, implement Pig Latin scripts for metadata analysis, and execute HiveQL queries to generate structured insights. The course blends practical scenarios with hands-on tools from the Hadoop ecosystem, empowering learners to analyze real-world data efficiently.
This project-based course offers a unique opportunity to practice Big Data analytics using actual YouTube data. Unlike theoretical courses, it emphasizes end-to-end implementation — from data preparation and transformation to query execution and output interpretation. Learners will gain practical skills in Hadoop, MapReduce, Pig, and Hive, making them proficient in handling complex datasets and extracting valuable insights.
By completing this course, learners will not only master essential Hadoop tools but also build a portfolio-ready project that demonstrates Big Data analysis skills applicable to industry scenarios such as video analytics, recommendation systems, and large-scale reporting. This makes the course ideal for students, professionals, and data enthusiasts aiming to strengthen their expertise in Big Data.
This module introduces learners to the fundamentals of Hadoop and MapReduce by exploring YouTube data analysis scenarios. It covers data preparation, Big Data basics, and the use of MapReduce to process large-scale datasets. Learners will gain hands-on insights into building analyzers that identify key patterns, high-rated videos, and structured outputs.
Inclus
10 vidéos3 devoirs
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10 vidéos•Total 87 minutes
Introduction to Youtube Data Analysis Using Hadoop•7 minutes
Introduction to Youtube Data Analysis Using Hadoop Continues•8 minutes
Data Preparation For Youtube Data Analysis using Hadoop•8 minutes
Basics of Big Data and Map Reduce•10 minutes
More on Big Data and Map Reduce•7 minutes
Working with Analysis Senario using Map Reduce•10 minutes
Example of Youtube Analyser using Map Reduce•9 minutes
Output Youtube Analyse in Map Reduces•7 minutes
High Rated Youtube Video Analyser in Map Reduces•12 minutes
Implementation and Outputt in Map Reduces•10 minutes
3 devoirs•Total 50 minutes
Graded - Hadoop and MapReduce Foundations•30 minutes
Introduction and Data Preparation•10 minutes
YouTube Analysis with MapReduce•10 minutes
Pig for YouTube Data Analysis
Module 2•2 heures à terminer
Détails du module
This module explores Apache Pig as a high-level tool for simplifying data transformations in Hadoop. Learners will understand Pig Latin scripting, its commands, and how to use Pig for analyzing YouTube metadata. Practical examples will demonstrate how Pig outputs structured insights from large datasets.
Inclus
5 vidéos3 devoirs
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5 vidéos•Total 49 minutes
Basics of PIG•10 minutes
Basics of PIG Continues•7 minutes
Analyze Youtube Data using PIG Implementation•10 minutes
Example of PIG Implementation•12 minutes
Output of PIG Implementation•9 minutes
3 devoirs•Total 50 minutes
Graded - Pig for YouTube Data Analysis•30 minutes
Fundamentals of Pig•10 minutes
Pig Implementation and Outputs•10 minutes
Hive for YouTube Data Analysis
Module 3•2 heures à terminer
Détails du module
This module covers Apache Hive and its SQL-like language HiveQL for large-scale YouTube data analysis. Learners will practice creating tables, running Hive queries, and generating aggregated insights such as top-rated or most-viewed videos. The module concludes with a summary of integrating Hadoop, MapReduce, Pig, and Hive for scalable data analytics.
Inclus
6 vidéos3 devoirs
Afficher les informations sur le contenu du module
6 vidéos•Total 47 minutes
Youtube Video Analyzer using Hive•7 minutes
Creating Youtube Video Analyzer using Hive•8 minutes
Analysis Youtube Videos using Hive Query•7 minutes
Analysis Youtube Videos using Hive Query Continues•6 minutes
More on Hive Query Languages•8 minutes
Conclusion•11 minutes
3 devoirs•Total 50 minutes
Graded - Hive for YouTube Data Analysis•30 minutes
Building YouTube Analyzer with Hive•10 minutes
Hive Queries and Course Conclusion•10 minutes
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