Introduction to Data Engineering
Master the data engineering lifecycle and build end-to-end data pipelines on AWS, from requirements gathering to implementation.
Master the data engineering lifecycle and build end-to-end data pipelines on AWS, from requirements gathering to implementation.
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 DeepLearning.AI Data Engineering Professional Certificate 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.
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What you'll learn
Understand the complete data engineering lifecycle
Implement batch and streaming data pipelines on AWS
Design robust data architectures following best practices
Translate stakeholder needs into system requirements
Master core data engineering principles and practices
Skills you'll gain
This course includes:
6.5 Hours PreRecorded video
6 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course introduces students to the complete data engineering lifecycle, from data generation to serving data to stakeholders. The curriculum covers essential concepts including data ingestion, transformation, storage, and pipeline development. Students gain hands-on experience with AWS cloud services, learning to design and implement both batch and streaming data pipelines. The course emphasizes practical skills in requirements gathering, system architecture, and data management principles.
Introduction to Data Engineering
Module 1 · 3 Hours to complete
The Data Engineering Lifecycle and Undercurrents
Module 2 · 4 Hours to complete
Data Architecture
Module 3 · 4 Hours to complete
Translating Requirements to Architecture
Module 4 · 5 Hours to complete
Fee Structure
Instructor
Leading Voice in Data Engineering and Best-Selling Author
Joe Reis is a prominent figure in data engineering, recognized as a best-selling author and a "recovering data scientist." He serves as a Data Engineer and Architect at DeepLearning.AI, where he also teaches courses on data engineering principles. Reis is the co-author of the acclaimed book "Fundamentals of Data Engineering" and is known for his engaging presentations as a global keynote speaker. His diverse roles include being a professor, podcaster, and writer, where he shares insights on effective data practices and the evolving landscape of data careers. Through his work, Reis aims to empower others in the field by providing practical knowledge and strategies for success in data engineering.
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4.8 course rating
114 ratings
Frequently asked questions
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