Data Engineering: Pipelines, ETL, Hadoop

$49
ENROLL NOWCourse Overview
What You'll Learn
- This course provides a comprehensive guide to mastering data engineering, where you'll learn to build robust data pipelines, delve into ETL (Extract, Transform, Load) processes, and handle large datasets using Hadoop.
- With hands-on experience in Hadoop, the industry-standard framework for handling massive datasets, you’ll learn to manage and process massive datasets efficiently.
- Whether you're a beginner or an experienced professional, this course equips you with the skills to design, implement, and manage data pipelines, making you a valuable asset in any data-focused organization.
This course provides a comprehensive guide to mastering data engineering, where you'll learn to build robust data pipelines, delve into ETL (Extract, Transform, Load) processes, and handle large datasets using Hadoop. You will gain expertise in extracting data from various sources, transforming it into a usable format, and loading it into data warehouses or big data platforms. With hands-on experience in Hadoop, the industry-standard framework for handling massive datasets, you’ll learn to manage and process massive datasets efficiently. Whether you're a beginner or an experienced professional, this course equips you with the skills to design, implement, and manage data pipelines, making you a valuable asset in any data-focused organization. This course is ideal for aspiring data engineers, software developers interested in data processing, and IT professionals looking to expand their expertise into data engineering. It is also suitable for business analysts and other professionals who seek a foundational understanding of data handling technologies to improve decision-making capabilities and enhance their roles in data-driven environments. Whether you are just starting your journey in data engineering or looking to strengthen your existing skills, this course will provide the knowledge and tools you need to succeed. To get the most out of this course, you should have a basic understanding of programming concepts and some familiarity with database systems. A foundational knowledge of Python programming and SQL will be helpful, as will an understanding of relational database systems. No prior experience with Hadoop is required, but a keen interest in big data and data analytics will greatly enhance your learning experience. By the end of this course, you will be able to analyze the architecture and components of data pipelines and understand their impact on data flow and processing efficiency. You will learn how to implement robust ETL processes that are scalable and maintainable, and you will be equipped to handle big data challenges using Hadoop’s ecosystem tools, such as HDFS, MapReduce, Hive, Pig, and Spark. This course will prepare you to design, implement, and manage data solutions that can drive meaningful insights and support strategic decision-making in any organization.
Course FAQs
Is this an accredited online course?
Accreditation for 'Data Engineering: Pipelines, ETL, Hadoop' is determined by the provider, Coursera Instructor Network. For online college courses or degree programs, we strongly recommend you verify the accreditation status directly on the provider's website to ensure it meets your requirements.
Can this course be used for continuing education credits?
Many of the courses listed on our platform are suitable for professional continuing education. However, acceptance for credit varies by state and licensing board. Please confirm with your board and {course.provider} that this specific course qualifies.
How do I enroll in this online school program?
To enroll, click the 'ENROLL NOW' button on this page. You will be taken to the official page for 'Data Engineering: Pipelines, ETL, Hadoop' on the Coursera Instructor Network online class platform, where you can complete your registration.





