Cloud Data Engineering Essentials
This course is part of Cloud Computing Basics Explained.
This comprehensive course covers essential data engineering principles for cloud environments. Learn to build scalable distributed systems, implement big data solutions, and develop serverless data pipelines. Gain practical experience with ETL processes, cloud databases, and storage systems. Master key concepts including data governance, security best practices, and modern data processing techniques. The course combines theoretical knowledge with hands-on labs using tools like AWS Lambda, Google BigQuery, and Databricks. Perfect for those looking to develop expertise in cloud-based data engineering solutions.
Instructors:
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What you'll learn
Build scalable distributed systems using cloud technologies
Implement big data solutions with modern processing techniques
Develop serverless data engineering pipelines
Master cloud ETL processes and data governance strategies
Optimize cloud databases and storage solutions
Apply security best practices in data engineering
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams, quizzes, labs
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 4 modules in this course
This comprehensive data engineering course focuses on cloud-native application development and modern data processing techniques. Students learn to build scalable distributed systems, implement big data solutions, and develop serverless data pipelines. The curriculum covers essential topics including ETL processes, cloud databases, storage systems, and data governance. Practical skills are developed through hands-on experience with industry-standard tools and platforms.
Methodologies in Data Engineering
Module 1
Principles of Data Engineering
Module 2
Building Data Engineering Pipelines
Module 3
Applying Key Data Engineering Tasks
Module 4
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Cloud Computing Basics Explained
Instructor
Executive in Residence and Founder of Pragmatic AI Labs at Duke University
Noah Gift is the founder of Pragmatic AI Labs and serves as an Executive in Residence at Duke University, where he lectures in the Master of Interdisciplinary Data Science (MIDS) program. He specializes in designing and teaching graduate-level courses on machine learning, MLOps, artificial intelligence, and data science, while also consulting on machine learning and cloud architecture for students and faculty. A recognized expert in the field, Gift is a Python Software Foundation Fellow and an AWS Machine Learning Hero, holding multiple AWS certifications, including AWS Certified Solutions Architect and AWS Certified Machine Learning Specialist. He has authored several influential books, such as Practical MLOps, Python for DevOps, and Pragmatic AI, and has published over 100 technical articles across various platforms, including Forbes and O'Reilly. His extensive industry experience includes roles as CTO and Chief Data Scientist for notable companies like Disney Feature Animation, Sony Imageworks, and AT&T, contributing to major films like Avatar and Spider-Man 3. Gift's work has generated millions in revenue through product development on a global scale. He actively consults startups on machine learning and cloud architecture while leading initiatives to enhance data science education.
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Frequently asked questions
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