In this course, you will be introduced to the data engineering lifecycle, from data generation in source systems, to ingestion, transformation, storage, and serving data to downstream stakeholders. You’ll study the key undercurrents that affect all stages of the lifecycle, and start developing a framework for how to think like a data engineer. To gain hands-on practice, you’ll gather stakeholder needs, translate those needs into system requirements, and choose tools and technologies to build systems that provide business value. By the end of this course you’ll be spinning up batch and streaming data pipelines to serve product recommendations on the AWS cloud!
Introduction to Data Engineering
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Introduction to Data Engineering
This course is part of DeepLearning.AI Data Engineering Professional Certificate
Instructors: Joe Reis
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Intermediate level
Recommended experience
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Gain a comprehensive understanding of the data engineering lifecycle and its undercurrents
Gather stakeholder needs and translate them into system requirements
Design and implement batch and streaming data pipelines on AWS
Skills you'll gain
Tools you'll learn
Details to know
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Assessments
6 assignments
Taught in English
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This course is part of the DeepLearning.AI Data Engineering Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from DeepLearning.AI
There are 4 modules in this course
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