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学生对 杜克大学 提供的 Cloud Data Engineering 的评价和反馈

36 个评分


Welcome to the third course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn how to apply Data Engineering to real-world projects using the Cloud computing concepts introduced in the first two courses of this series. By the end of this course, you will be able to develop Data Engineering applications and use software development best practices to create data engineering applications. These will include continuous deployment, code quality tools, logging, instrumentation and monitoring. Finally, you will use Cloud-native technologies to tackle complex data engineering solutions. This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering. Students should have beginner level Linux and intermediate level Python skills. For your project in this course, you will build a serverless data engineering pipeline in a Cloud platform: Amazon Web Services (AWS), Azure or Google Cloud Platform (GCP)....

1 - Cloud Data Engineering 的 10 个评论(共 10 个)

创建者 Joshua S

Nov 5, 2021

They should add more examples using the tools and services, however Iearned a lot of thing related to data engineering an the aws cloud, I think this knowledge is going to be very useful in my professional dimesion

创建者 dave t

Apr 10, 2022

I am only on week 1 but already I have lots of suggestions. This course could be improved by

1. If you use an acronym explain what it stands for.

2. Make it very clear where the gists, github repos are.

3. Some advice provided is out of date or not good advice. Debugging lambdas can be done using other approaches which have zero cost and do not tie you into a specific vendor (e.g. GitHub ). I have left comments in the discusssion forum on this.

4. Improve the explanations and content , testing isn't covered at all well. Why is Pytest ( a dependency) better than Unittest (a cor elibrary) I agree its beter but what if I do not know, what should I test and how. All this wasn't covered and it wasn't made clear I should know it.

5. Improve editing , in some lectures the lecturer is answering questions and there are a lot of gaps between the answers and unheard questions.

6. Imporve the delivery, sometimes the explanations provided are unclear or lack good reasons why the course of action is being taken.

7. Provide more hands on labs.

创建者 Pineapple P

Jul 24, 2021

Material covered mostly on the surface level.

创建者 Taozheng Z

Jul 2, 2021

Need to be revised

创建者 Renato M

Jun 15, 2022

G​reat course

创建者 Rogério A

Dec 31, 2021

Very important information and concepts was shared.

创建者 dumebi j

Nov 16, 2021


创建者 Alejandro A

Aug 1, 2022

It doesn't provide labs for AWS

创建者 Andrés C

Nov 13, 2021

A lot of reused material, a lot of random stuff and just jumping to examples without actually giving context.

创建者 Holly S

May 5, 2022

no inbuilt labs