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


Instructors: Joe Reis +1 more
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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
- Category: Network Troubleshooting
- Category: Data Integration
- Category: CI/CD
- Category: Data Transformation
- Category: Data Pipelines
- Category: Infrastructure as Code (IaC)
- Category: Data Quality
- Category: Data Processing
- Category: IT Automation
- Category: Extract, Transform, Load
Tools you'll learn
- Category: NoSQL
- Category: Amazon Web Services
- Category: Apache Airflow
- Category: Amazon CloudWatch
- Category: Terraform
Details to know

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4 assignments
Build your Cloud Computing expertise
- 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 136
Reviewed on Dec 19, 2025
its good , time has change to write code urself , if you can understand code than you can do it
Reviewed on Jan 18, 2025
great learning and exercises. appreciate the community.
Reviewed on Mar 23, 2025
best course and best projects to practice for data engineering