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Learner Reviews & Feedback for Source Systems, Data Ingestion, and Pipelines by DeepLearning.AI

4.7
stars
30 ratings

About the Course

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....

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1 - 7 of 7 Reviews for Source Systems, Data Ingestion, and Pipelines

By Francisco Z L

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Oct 24, 2024

Amazing course, very complete. I learned and tuned many new techniques and good practices to improve my data engineering activities. Really liked the content, and the Labs will take you at least 15 hours to complete, but you will understand how to apply this new knowledge. Learned a few new things about Terraform, and Airflow will be a very valuable tool for my future projects.

By Iain N H

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Nov 15, 2024

Excellent course, with up to date technology, interesting labs and challenging quizzes. Highly recommended.

By rashid a

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Nov 20, 2024

All concepts related to these topics are explained clearly.

By Yosef A

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Oct 30, 2024

Great balance between theory and practice.

By Pavel N

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Nov 16, 2024

Outstanding course. Labs are great !

By Younes A

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Nov 17, 2024

The course theory is good but it focuses on general concepts. This is a big jump from the material to the lab where you will find yourself with ready jupyter files with missing variable names that you fill to have the exercice done. This approach is not stimulating the learning. It's too passive.

By Syd F

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Nov 1, 2024

You will not write code in this course. You will perform the most rudimentary code replacements in functions (IE replace "None" with "table_name", this isn't even a joke, see Week 1 Lab 2) and run Jupyter Notebook cells that are already written for you. Truly disappointed.