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+ <!DOCTYPE html>
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+ < html lang ="en ">
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+ < head >
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+ < meta charset ="UTF-8 ">
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+ < meta name ="viewport " content ="width=device-width, initial-scale=1.0 ">
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+ < title > Apache Spark and Databricks for Beginners - ITVersity</ title >
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+ < link rel ="stylesheet " href ="../styles.css ">
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+ < link rel ="stylesheet " href ="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css ">
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+ </ head >
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+ < body >
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+ < header >
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+ < nav >
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+ < div class ="logo "> ITVersity</ div >
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+ < ul class ="nav-links ">
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+ < li > < a href ="../index.html "> Home</ a > </ li >
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+ < li > < a href ="../index.html#services "> Services</ a > </ li >
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+ < li > < a href ="../index.html#courses "> Courses</ a > </ li >
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+ < li > < a href ="../index.html#locations "> Locations</ a > </ li >
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+ < li > < a href ="../index.html#contact "> Contact</ a > </ li >
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+ </ ul >
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+ </ nav >
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+ </ header >
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+
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+ < section class ="course-hero spark-hero ">
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+ < div class ="hero-content ">
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+ < h1 > Apache Spark and Databricks for Beginners</ h1 >
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+ < p > Learn big data processing with Apache Spark and master the Databricks platform</ p >
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+ < a href ="../index.html#contact " class ="cta-button "> Enroll Now</ a >
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+ </ div >
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+ </ section >
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+
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+ < section class ="course-details ">
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+ < div class ="container ">
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+ < h2 > Course Overview</ h2 >
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+ < div class ="course-grid ">
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+ < div class ="course-info ">
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+ < h3 > What You'll Learn</ h3 >
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+ < ul >
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+ < li > < i class ="fas fa-check "> </ i > Apache Spark architecture and components</ li >
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+ < li > < i class ="fas fa-check "> </ i > Databricks workspace and notebooks</ li >
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+ < li > < i class ="fas fa-check "> </ i > Data processing with Spark SQL</ li >
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+ < li > < i class ="fas fa-check "> </ i > Spark DataFrames and Datasets</ li >
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+ < li > < i class ="fas fa-check "> </ i > Machine learning with MLlib</ li >
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+ < li > < i class ="fas fa-check "> </ i > Stream processing fundamentals</ li >
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+ < li > < i class ="fas fa-check "> </ i > Delta Lake for reliable data lakes</ li >
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+ < li > < i class ="fas fa-check "> </ i > Performance optimization and monitoring</ li >
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+ </ ul >
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+ </ div >
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+ < div class ="course-features ">
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+ < h3 > Course Features</ h3 >
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+ < div class ="feature-cards ">
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+ < div class ="feature-card ">
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+ < i class ="fas fa-clock "> </ i >
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+ < h4 > Duration</ h4 >
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+ < p > 10 Weeks</ p >
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+ </ div >
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+ < div class ="feature-card ">
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+ < i class ="fas fa-video "> </ i >
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+ < h4 > Format</ h4 >
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+ < p > Live Online Classes</ p >
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+ </ div >
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+ < div class ="feature-card ">
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+ < i class ="fas fa-certificate "> </ i >
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+ < h4 > Certificate</ h4 >
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+ < p > Industry Recognized</ p >
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+ </ div >
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+ < div class ="feature-card ">
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+ < i class ="fas fa-users "> </ i >
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+ < h4 > Batch Size</ h4 >
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+ < p > Maximum 15 Students</ p >
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+ </ div >
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+ </ div >
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+ </ div >
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+ </ div >
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+ </ div >
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+ </ section >
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+
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+ < section class ="course-curriculum ">
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+ < div class ="container ">
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+ < h2 > Curriculum</ h2 >
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+ < div class ="curriculum-weeks ">
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+ < div class ="week ">
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+ < h3 > Week 1-2: Foundations</ h3 >
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+ < ul >
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+ < li > Introduction to Big Data and Spark</ li >
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+ < li > Spark architecture and components</ li >
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+ < li > Setting up Databricks workspace</ li >
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+ < li > Working with Databricks notebooks</ li >
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+ </ ul >
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+ </ div >
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+ < div class ="week ">
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+ < h3 > Week 3-4: Data Processing</ h3 >
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+ < ul >
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+ < li > Spark SQL and DataFrames</ li >
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+ < li > Data transformation and aggregation</ li >
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+ < li > Working with different data formats</ li >
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+ < li > Performance optimization techniques</ li >
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+ </ ul >
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+ </ div >
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+ < div class ="week ">
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+ < h3 > Week 5-7: Advanced Features</ h3 >
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+ < ul >
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+ < li > Machine learning with MLlib</ li >
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+ < li > Stream processing basics</ li >
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+ < li > Delta Lake fundamentals</ li >
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+ < li > Data quality and testing</ li >
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+ </ ul >
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+ </ div >
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+ < div class ="week ">
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+ < h3 > Week 8-10: Production & Projects</ h3 >
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+ < ul >
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+ < li > Production deployment patterns</ li >
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+ < li > Monitoring and optimization</ li >
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+ < li > Best practices and patterns</ li >
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+ < li > Capstone project</ li >
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+ </ ul >
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+ </ div >
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+ </ div >
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+ </ div >
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+ </ section >
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+
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+ < section class ="course-projects ">
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+ < div class ="container ">
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+ < h2 > Industry Projects</ h2 >
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+ < div class ="project-cards ">
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+ < div class ="card ">
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+ < img src ="https://images.unsplash.com/photo-1551288049-bebda4e38f71?ixlib=rb-1.2.1&auto=format&fit=crop&w=800&q=80 " alt ="Data Analysis Project " class ="project-image ">
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+ < i class ="fas fa-chart-line "> </ i >
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+ < h3 > Data Analysis Pipeline</ h3 >
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+ < p > Build an end-to-end data analysis pipeline using Spark</ p >
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+ </ div >
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+ < div class ="card ">
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+ < img src ="https://images.unsplash.com/photo-1518186285589-2f7649de83e0?ixlib=rb-1.2.1&auto=format&fit=crop&w=800&q=80 " alt ="ML Project " class ="project-image ">
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+ < i class ="fas fa-brain "> </ i >
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+ < h3 > ML Model Deployment</ h3 >
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+ < p > Deploy machine learning models using MLlib</ p >
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+ </ div >
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+ < div class ="card ">
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+ < img src ="https://images.unsplash.com/photo-1558494949-ef010cbdcc31?ixlib=rb-1.2.1&auto=format&fit=crop&w=800&q=80 " alt ="Streaming Project " class ="project-image ">
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+ < i class ="fas fa-stream "> </ i >
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+ < h3 > Real-time Analytics</ h3 >
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+ < p > Build a real-time analytics dashboard</ p >
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+ </ div >
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+ </ div >
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+ </ div >
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+ </ section >
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+
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+ < footer >
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+ < div class ="footer-content ">
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+ < div class ="footer-section ">
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+ < h4 > ITVersity, Inc</ h4 >
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+ < p > Empowering careers through quality education</ p >
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+ </ div >
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+ < div class ="footer-section ">
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+ < h4 > Quick Links</ h4 >
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+ < ul >
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+ < li > < a href ="../index.html "> Home</ a > </ li >
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+ < li > < a href ="../index.html#courses "> All Courses</ a > </ li >
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+ < li > < a href ="../index.html#contact "> Contact</ a > </ li >
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+ </ ul >
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+ </ div >
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+ < div class ="footer-section ">
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+ < h4 > Connect With Us</ h4 >
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+ < div class ="social-links ">
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+ < a href ="# "> < i class ="fab fa-linkedin "> </ i > </ a >
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+ </ div >
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+ </ div >
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+ </ div >
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+ < div class ="footer-bottom ">
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+ < p > © 2024 ITVersity, Inc. All rights reserved.</ p >
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+ </ div >
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+ </ footer >
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+ </ body >
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+ </ html >
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