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Data Engineering Course Online - With Hadoop and Spark
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The Data Engineering Online Course - with Hadoop and Spark is designed to help you master the skills needed for a successful career in data engineering. This course covers essential concepts such as big data processing, distributed systems, and data pipelines using powerful tools like Hadoop and Spark. Perfect for beginners and professionals, this course helps you build a solid foundation in data engineering and prepare for high-demand roles in the tech industry.
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What people say about Three-90 Challenge
Abhay Gupta
"I am so glad I took this challenge – it has completely transformed my life. The competitive deadline kept me focused, allowing me to complete the course within 90 days, which greatly helped in my campus placement preparation. As a result, I secured a position at my dream company. I will always recommend this challenge to others! ✨❣️ Feeling so happy!.₹5399 RefundedView All -->- Pranay Chhetri"The Three 90 challenge was great because as long as one completes the course within 90 days of purchasing the course and fills out the form upon completion, 90% of the amount paid is refunded in about two weeks. Not to mention the courses are helpful as you get to learn a lot.₹1799 RefundedView All -->
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Course Overview
Start your data engineering journey with the GeeksforGeeks Online Data Engineering Program. With this course, you'll acquire essential data engineering knowledge and expertise, positioning you for success in this fast-growing industry.
This complete Data Engineering Course begins by introducing you to the basics of data engineering, focusing on how to set up a development environment using Hadoop and Spark. You'll learn to navigate the Hadoop Distributed File System (HDFS) and tackle simple MapReduce jobs to understand data processing fundamentals. The Data Engineering course also covers YARN (Yet Another Resource Negotiator), which helps manage resources in clusters.
Youll also gain hands-on experience with cluster management, learning how to set up, monitor, and maintain a Spark cluster.
Data Engineering Course - Highlights:
- 10hrs+ video content and articles/notice to learn the concepts
- 200+ MCQs to practice your knowledge
- Fundamentals of Hadoop and Spark, setting up a local development environment.
- Develop a working knowledge of NoSQL & Big Data using Hadoop, Apache Spark
- Learn ML with Spark MLlib and graph processing with GraphX
- Learn to set up and manage a Spark cluster and debug Spark applications.
- Hands-on:
- Running a simple MapReduce job | Hands-on: Working with HDFS and running a basic MapReduce job
- Writing and running Spark applications with Python
- Working with Spark DataFrames and performing SQL queries
- Building a simple Spark Streaming application
- Developing a PySpark application with Python
- Building and analyzing a graph using Spark GraphX
- Designing and implementing a simple data warehouse
- Building a basic ETL pipeline
- Working with a data lake
- Building a Kafka-Powered Data Pipeline
Course Content
- Course Introduction
- Overview of Data Engineering
- Introduction to Hadoop and Spark
- Setting up a development environment with Hadoop and Spark
- Hands-on: Installing Hadoop and Spark locally
- Understanding Hadoop Distributed File System (HDFS)
- Hadoop MapReduce paradigm
- Introduction to YARN (Yet Another Resource Negotiator)
- Running a simple MapReduce job | Hands-on: Working with HDFS and running a basic MapReduce job
- Overview of Apache Spark
- Spark architecture and components
- Spark RDD (Resilient Distributed Datasets)
- Transformations and Actions in Spark
- Hands-on: Writing and running Spark applications with Python
- Introduction to Spark DataFrames
- Spark SQL for querying structured data
- Basic DataFrame operations
- Optimizations in Spark DataFrames
- Hands-on: Working with Spark DataFrames and performing SQL queries
Course Instructor
Data Engineer Consultant at Deloitte USI
He is an experienced Data Engineering Consultant with over 5+ years of expertise in the IT Services and Consulting industry. Currently working at Deloitte USI, he specializes in the ingestion, storage, processing, querying, and analysis of big data. With hands-on experience across major cloud platforms like AWS and Azure, he brings deep technical knowledge in data engineering, enabling him to design and implement robust data pipelines, optimize workflows, and leverage cloud services to handle complex data processing tasks at scale.
Having earned certifications from both AWS and Microsoft, he is equipped with the latest industry knowledge and best practices in cloud technologies and data engineering. His passion for data and problem-solving, combined with his extensive hands-on experience, makes him an excellent mentor for individuals looking to grow in the fields of big data, cloud computing, and data engineering.
Pricing
$ 60
