Big Data Hadoop Course 2024

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Free Download Big Data Hadoop Course 2024
Published 1/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 333.51 MB | Duration: 0h 41m
Mastering Big Data: A Comprehensive Guide to Hadoop Online Courses

What you'll learn
Industry-Relevant Curriculum: Courses designed to meet industry demands.
Real-world Case Studies: Analyzing real-world scenarios to develop problem-solving skills.
Hadoop enables the seamless addition of nodes to a cluster, making it highly scalable to handle increasing data loads.
The open-source nature of Hadoop eliminates the need for expensive hardware, making it a cost-effective solution for Big Data processing.
Requirements
Basic Programming Knowledge: Understanding of languages like Java, Python, or Scala.
Database and SQL Skills: Familiarity with databases and SQL is beneficial.
Linux Fundamentals: Basic knowledge of Linux commands and operations.
Description
Introduction: Welcome to the era of Big Data, where the ability to analyze and manage vast amounts of information is a crucial skill in the professional world. Hadoop, an open-source framework, has emerged as a game-changer in the field of Big Data processing and analytics. In this blog post, we'll take a deep dive into the world of Hadoop online courses, exploring their overview, benefits, target audience, career scope, salary packages, requirements, key features, and certification options.Overview of Hadoop:Hadoop is a distributed storage and processing framework designed to handle large-scale data sets across clusters of computers. It comprises two main components - Hadoop Distributed File System (HDFS) for storage and MapReduce for processing. With its ability to scale horizontally, Hadoop is ideal for processing and analyzing massive datasets efficiently.Benefits of Learning Hadoop:Scalability: Hadoop enables the seamless addition of nodes to a cluster, making it highly scalable to handle increasing data loads.Cost-Effective: The open-source nature of Hadoop eliminates the need for expensive hardware, making it a cost-effective solution for Big Data processing.Fault Tolerance: Hadoop's distributed nature ensures fault tolerance, with data replicated across multiple nodes, reducing the risk of data loss.Who Can Learn Hadoopata Professionals: Data scientists, analysts, and engineers looking to enhance their skills in managing and analyzing large datasets.IT Professionals: System administrators and developers interested in understanding and implementing Big Data solutions.Business Analysts: Professionals aiming to extract valuable insights from data to drive business decisions.Career Scope:The demand for Hadoop professionals is on the rise across various industries, including finance, healthcare, e-commerce, and more. Job roles may include:Big Data EngineerHadoop DeveloperData ScientistBusiness Intelligence AnalystSalary Package with Job Roles in India and Abroad:In India, entry-level Hadoop professionals can expect salaries ranging from INR 5-8 lakhs per annum, with experienced professionals earning upwards of INR 15 lakhs. Abroad, salaries can range from $70,000 to $120,000 per annum, depending on experience and location.
Overview
Section 1: Introduction
Lecture 1 1.1. Overview and Market Trenda of Hadoop
Lecture 2 1.2. What is Hadoop
Lecture 3 1.3. What is Big Data
Lecture 4 1.4. Big Data Application Example in Different Industries
Lecture 5 1.5. Hadoop Ecosystem
Section 2: Big Data and Characteristics
Lecture 6 2.1. Big Data and Characteristics
Section 3: Common Big Data Customer Scenarios
Lecture 7 3.1. Common Big Data Customer Scenarios
Section 4: Hadoop and Distributed File System
Lecture 8 4.1. Distributed File System (DFS)
Lecture 9 4.2. Hadoop & It Structure and Characteristics
Data Professionals: Data scientists, analysts, and engineers looking to enhance their skills in managing and analyzing large datasets.,IT Professionals: System administrators and developers interested in understanding and implementing Big Data solutions.,Business Analysts: Professionals aiming to extract valuable insights from data to drive business decisions.


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