In this course, you will explore various types of source systems, learn how they generate and update data, and troubleshoot common issues you might encounter when trying to connect to these systems in the real world. You’ll dive into the details of common ingestion patterns and implement batch and streaming pipelines. You’ll automate and orchestrate your data pipelines using infrastructure as code and pipelines as code tools. You’ll also explore AWS and open source tools for monitoring your data systems and data quality.
Source Systems, Data Ingestion, and Pipelines
Source Systems, Data Ingestion, and Pipelines
This course is part of DeepLearning.AI Data Engineering Professional Certificate
Instructor: Joe Reis
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Gain insight into a topic and learn the fundamentals.
134 reviews
Intermediate level
Recommended experience
Flexible schedule
3 weeks at 10 hours a week
Learn at your own pace
92%
Most learners liked this course
What you'll learn
Gather stakeholder needs and translate them into system requirements.
Implement a batch and a streaming ingestion process on AWS to ingest data from various source systems.
Integrate aspects of security, data management, DataOps and orchestration into the data systems you build.
Skills you'll gain
Tools you'll learn
Details to know
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Add to your LinkedIn profile
Assessments
4 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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Showing 3 of 134
FW
Reviewed on Dec 19, 2025
its good , time has change to write code urself , if you can understand code than you can do it
DD
Reviewed on Mar 23, 2025
best course and best projects to practice for data engineering
MH
Reviewed on Jun 8, 2025
to the point and clear information related to that how data systems work and ingestion process and pipleine that is the main crux of the data engineering
