What will you in the Introduction to Big Data Course
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Understand the Big Data landscape, including real-world applications and challenges
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Identify the key characteristics of Big Data, often referred to as the 6 V’s: Volume, Velocity, Variety, Veracity, Valence, and Value
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Apply a structured 5-step process to analyze Big Data effectively
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Differentiate between Big Data problems and traditional data challenges
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Gain foundational knowledge of Hadoop’s architecture, including HDFS, YARN, and MapReduce
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Install and execute a simple program using Hadoop for hands-on experience
Program Overview
1. Welcome
Duration: 25 minutes
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Introduction to the Big Data Specialization and course objectives
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Engagement with the course community through discussion prompts
2. Big Data: Why and Where
Duration: 4 hours
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Exploration of the origins and significance of Big Data
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Examination of data sources: people, organizations, and sensors
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Case studies highlighting Big Data applications in various sectors
3. Characteristics of Big Data and Dimensions of Scalability
Duration: 2 hours
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In-depth analysis of the 6 V’s of Big Data
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Discussion on scalability challenges and solutions in Big Data systems
4. Data Science: Getting Value out of Big Data
Duration: 3 hours
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Introduction to the data science process tailored for Big Data
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Steps include data acquisition, exploration, preprocessing, analysis, and communication of results
5. Foundations for Big Data Systems and Programming
Duration: 1 hour
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Overview of distributed file systems and scalable computing
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Introduction to programming models suitable for Big Data processing
6. Systems: Getting Started with Hadoop
Duration: 5 hours
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Detailed look into Hadoop’s ecosystem and its components
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Hands-on assignment involving the installation and execution of a simple Hadoop program
Get certificate
Job Outlook
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Aspiring Data Professionals: Build a strong foundation in Big Data concepts and tools
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Business Analysts: Enhance analytical skills by understanding Big Data applications
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IT Professionals: Gain insights into Big Data infrastructure and processing frameworks
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Researchers: Leverage Big Data methodologies for data-driven research
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Students: Prepare for advanced studies in data science and analytics
Explore More Learning Paths
Expand your knowledge in big data technologies and analytics with these carefully curated courses designed to help you process, analyze, and manage large-scale datasets effectively.
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Big Data Specialization Course – Gain a comprehensive understanding of big data concepts, tools, and applications for real-world scenarios.
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Big Data Integration and Processing Course – Learn to integrate and process massive datasets efficiently using modern big data technologies.
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Data Engineering, Big Data, and Machine Learning on GCP Specialization Course – Develop advanced skills in data engineering, big data analytics, and machine learning using Google Cloud Platform.
Related Reading
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What Is Data Management? – Understand data management practices that are essential for handling and analyzing big data effectively.
