Master cloud-based data engineering with hands-on training in ETL, serverless pipelines, and distributed systems. Perfect for Python developers.
Master cloud-based data engineering with hands-on training in ETL, serverless pipelines, and distributed systems. Perfect for Python developers.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Building Cloud Computing Solutions at Scale Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.1
(73 ratings)
12,182 already enrolled
Instructors:
English
What you'll learn
Develop distributed systems for data engineering applications
Build serverless data engineering pipelines in cloud platforms
Implement ETL processes and data governance practices
Create efficient command-line data processing tools
Manage cloud databases and storage solutions
Skills you'll gain
This course includes:
11.75 Hours PreRecorded video
16 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course focuses on applying data engineering principles to real-world projects using cloud computing. Students learn to develop data engineering applications using software development best practices, including continuous deployment, code quality tools, and monitoring. The curriculum covers serverless data engineering, ETL processes, cloud databases, and storage solutions while emphasizing hands-on experience with building data pipelines in major cloud platforms.
Getting Started with Cloud Data Engineering
Module 1 · 12 Hours to complete
Examining Principles of Data Engineering
Module 2 · 11 Hours to complete
Building Data Engineering Pipelines
Module 3 · 6 Hours to complete
Applying Key Data Engineering Tasks
Module 4 · 10 Hours to complete
Fee Structure
Instructor
Executive in Residence and Founder of Pragmatic AI Labs
Noah Gift is the founder of Pragmatic AI Labs and serves as an Executive in Residence at Duke University, where he lectures in the MIDS Graduate Data Science Program. With nearly two decades of experience, he specializes in machine learning, MLOps, and cloud architecture, designing graduate-level courses that bridge theory and practical applications. Gift is a recognized expert in the field, being a Python Software Foundation Fellow and an AWS Machine Learning Hero, with extensive experience working with major companies such as Disney Feature Animation, Sony Imageworks, and AT&T. He has authored several influential books, including Practical MLOps and Python for DevOps, and has published numerous technical articles across various platforms.In his teaching role, Gift offers a wide range of courses such as Advanced Data Engineering, Cloud Machine Learning Engineering and MLOps, and Data Visualization with Python. His work emphasizes hands-on learning and real-world problem-solving using contemporary tools in AI and cloud computing. By leveraging his industry experience and academic insights, Gift aims to equip students with the skills necessary to tackle complex challenges in data science and machine learning, preparing them for successful careers in these rapidly evolving fields.
Testimonials
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4.1 course rating
73 ratings
Frequently asked questions
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