Why this course?

Description

Are you working with Big Data and looking for a powerful yet flexible tool to explore, analyze, and visualize your data? Do you want to build interactive dashboards, run Spark jobs, and connect with multiple big data sources — all within a single notebook environment? If yes, then this course is designed for you.

Apache Zeppelin is a modern, web-based notebook that brings data exploration, visualization, analytics, and collaboration together. Unlike traditional notebooks, Zeppelin is built for Big Data. It allows you to seamlessly integrate with Apache Spark, Hadoop, Hive, Kafka, MySQL, HDFS, S3, and more, while also supporting multiple interpreters like Scala, Python, SQL, and Shell.

In this hands-on, project-driven course, you will not only master Zeppelin’s core features but also learn how to integrate it into real-world Big Data workflows. Starting with installation and setup (on both Ubuntu and Windows using Docker), you will move step by step into mastering notebooks, interpreters, dynamic visualizations, and Spark integration.

You will then progress to working with external data sources, building ETL pipelines, and connecting Zeppelin with tools like Kafka and Hive. By the end, you’ll put your skills into action with Capstone Projects, including Telecom Customer Churn Prediction and a Real-Time Log Analytics Dashboard powered by Kafka, Spark, MySQL, and Zeppelin visualizations.

This course ensures that you go beyond theory — you will be working with real datasets, writing real code, and building real-world data engineering and analytics solutions.

 

What makes this course different?

• Entirely hands-on with practical examples at every step
• Focused on Big Data integration and real-world use cases
• Includes multiple capstone projects to give you job-ready skills
• Covers both beginners and intermediate data engineers with progressive learning

 

By the end of this course, you will have mastered how to:

 

• Install and configure Apache Zeppelin on Ubuntu and Windows (via Docker)
• Understand Zeppelin’s architecture, features, and benefits
• Work with Notebooks, Paragraphs, Markdown, and Dynamic Forms
• Build rich data visualizations (tables, bar, pie, line charts, etc.)
• Configure and connect Zeppelin interpreters (Spark, Python, JDBC, Hive, Shell)
• Run and visualize Apache Spark jobs using Zeppelin (RDDs, DataFrames, SQL)
• Connect to external data sources: HDFS, S3, JDBC, MySQL, Hive
• Perform data cleaning, transformation, and exploration in Spark Scala
• Create modular ETL pipelines with parameterization and documentation
• Integrate Zeppelin with Kafka, Hadoop, and MLlib for advanced analytics
• Work on Capstone Projects:

1. Telecom Customer Churn Prediction using Machine Learning in Spark
2. Real-Time Log Analytics Dashboard with Kafka, Spark, MySQL, and Zeppelin

This course is your complete end-to-end guide to mastering Apache Zeppelin for Big Data visualization, analytics, and real-world data engineering projects. Whether you are a beginner exploring data notebooks or a professional data engineer looking to build scalable pipelines, this course will give you the skills and confidence to apply Zeppelin in production-level scenarios.

 

What will students learn in your course?

• Understand the core concepts, features, and architecture of Apache Zeppelin
• Install and configure Zeppelin on Ubuntu and Windows (via Docker)
• Create and manage Notebooks, Paragraphs, and Dynamic Forms for interactive data exploration
• Use Markdown effectively to document and present insights within Zeppelin
• Build rich visualizations (tables, bar charts, pie charts, line graphs, scatter plots, etc.) directly inside notebooks
• Configure and work with multiple interpreters (Spark, Python, JDBC, Hive, Shell, etc.)
• Run Apache Spark jobs (RDDs, DataFrames, SQL queries) inside Zeppelin notebooks
• Load, clean, transform, and explore large datasets from HDFS, S3, JDBC, and MySQL
• Build ETL pipelines in Zeppelin using Spark Scala and parameterized workflows
• Integrate Zeppelin with Hive, Kafka, and other Big Data tools
• Perform machine learning tasks in Zeppelin using Spark MLlib
• Develop modular notebooks for better reusability and collaboration
• Export notebooks and results in multiple formats (HTML, PDF, etc.)
• Work on real-world capstone projects including:
• Telecom Customer Churn Prediction using Spark MLlib in Zeppelin
• Real-Time Log Analytics Dashboard using Kafka, Spark, MySQL, and Zeppelin visualizations