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Learner Reviews & Feedback for Data Modeling, Transformation, and Serving by DeepLearning.AI

4.5
stars
24 ratings

About the Course

In this course, you’ll model, transform, and serve data for both analytics and machine learning use cases. You’ll explore various data modeling techniques for batch analytics, including normalization, star schema, data vault, and one big table, and you’ll use dbt to transform a dataset based on a star schema and one big table. You’ll also compare the Inmon vs Kimball data modeling approaches for data warehouses. You’ll model and transform a tabular dataset for machine learning purposes. You’ll also model and transform unstructured image and textual data. You’ll explore distributed processing frameworks such as Hadoop MapReduce and Spark, and perform stream processing. You’ll identify different ways of serving data for analytics and machine learning, including using views and materialized views, and you’ll describe how a semantic layer built on top of your data model can support the business. In the last week of this course, you’ll complete a capstone project where you’ll build an end-to-end data pipeline that encompasses all of the stages of the data engineering lifecycle to serve data that provides business value....

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1 - 4 of 4 Reviews for Data Modeling, Transformation, and Serving

By Cheong W L

•

Sep 30, 2024

This course is terrible. For the 2 assignments there are a lot of file that need to complete the code. But only give 2 hours time for these two assignment. I unable to complete the assignments due to limited time. Th instructor should let the learner to extend the time if needed. This is not a free course. This is pay course in order to get the certification. I don't understand why give tons of file to complete the code but never give learner to extend time for the assignment. I don't mind to do a lot of exercise but the problem that I need is more time.

By rashid a

•

Nov 20, 2024

Final capstone project combined all learn concepts.

By Libby L

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Nov 7, 2024

Really like it.

By Piyush P

•

Sep 29, 2024

I think this course is trying to cover a lot more than it should. If I am not wrong, that's true for all courses in this specialization. I don't think it's suitable for beginners or even so called intermediate data engineers.