Data Engineering, Big Data, and Machine Learning on GCP

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Below are the top discussions from Reddit that mention this online Coursera specialization from Google Cloud.

This five-week, accelerated online specialization provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform.

Tensorflow Bigquery Bigtable Dataflow Google Cloud Platform Cloud Computing Google Cloud Dataproc Application Programming Interfaces (API) Machine Learning Apache Beam Publish–Subscribe Pattern Feature Engineering

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Taught by
Google Cloud Training

and 13 more instructors

Offered by
Google Cloud

This specialization includes these 1 courses.

Reddit Posts and Comments

2 posts • 14 mentions • top 9 shown below

r/datascience • post
28 points • polpenn
Thoughts on the "Data Engineering on Google Cloud Platform Specialization" from Coursera?

Here's the link to the specialization:

I'm thinking about paying for the entire specialization to learn how to deploy machine learning on an offsite server. I tried reading the documentation and working with the examples from the Google Cloud Platform website but I still feel lost about how everything fits together. I have taken a few machine learning courses but I feel completely loss when it comes to this stuff. Any thoughts on this specialization?

r/googlecloud • comment
6 points • burgerboy9n

Hey there! I work on Google Cloud. You should checkout our courses on Coursera. For example, here is our Data Engineering, Big Data, and Machine Learning . Let me know if you have any questions.

r/googlecloud • post
5 points • fhoffa
Coursera: Data Engineering on Google Cloud Platform Specialization
r/dataengineering • comment
3 points • joshlaird

I was surprised as 20% of the exam were machine learning questions; not just on the ML services but ML theory such as ways to reduce loss. Other surprise was a few questions on Stackdriver to see how your different services are performing.

I use GCP daily in my job so I had it easier but I'd say the best way to revise is to get your hands dirty using the services.

There are also multiple courses out there, in particular the Data Engineering course provided by Google themselves on Coursera was great: As this course gives you theory as well as hands on practice

r/googlecloud • post
5 points • johnreese421
"Associate Cloud Engineer" and "Associate cloud engineer"

Hello all. I am willing to get GCP certified which would add some weight on my resume.

So, I am still in way of gathering material/resources to start on.

According to my understanding of looking up various things online : first step having "Associate Cloud Engineer" certification and then going for "Professional Data Engineer" certification is a good way .

what are your thoughts on it.? and would the coursera course link ( ) be good enough for passing both the certifications or separate course is to be done for "Associate cloud engineer" certification.?

Please let me know if you have any other resources/material suggestions .

r/dataengineering • comment
3 points • _WeWereHere

Great idea, thanks for putting this together. You could add the two courses on Coursera and Udacity:

r/cscareerquestions • comment
1 points • ASamir

The intern position had these in the requirements:

1- You’ve dabbled in high volume data, preferably with distributed systems such as Hadoop, BigTable, and Cassandra.

2- You’ve had exposure to data modeling, data access, and data storage techniques.

I signed up to take Google Cloud's Coursera Specialization " Data Engineering on Google Cloud Platform" but I still don't think it's enough. The application deadline is almost 2 months from today! Other than being confident in using Python and SQL, I'm looking for project ideas that could help me demonstrate my skills and interest in being a data engineer.

r/dataengineering • comment
1 points • ethanenglish

If you're learning Google Cloud Platform, I'd suggest this Coursera course:

r/learnmachinelearning • comment
1 points • DataNerd555


I don't know if you have the funds, but I would recommend checking out the data engineering nano-degree at udacity. If you apply during these times you can get a 40% discount because of COVID-19. This should give you the basics.


Long Version:

I think you made a good call with data engineering, this is a really good role and frankly not enough people are applying for this kind of job. Too many people are trying for data science which is getting very saturated, but data engineering has plenty of void that needs to be filled.

Your work experience as a bank teller and a VW sales representative are not tech, which is bad, but you need to tell your employer during the interview that it show cases that you understand the working environment, how to communicate and collaborate with others and all the rest of those soft skills.

As far as the degree goes, you don't really need more schooling. What you need is proven experience that you can get the job done. For that, you need to convince the employer. Most employers will evaluate you based on:

- experience (not an option in this case),

- interview challenges (totally possible to prepare) [go to leetcode or find practice data engineering interview questions online]

- past projects (totally possible to prepare). [udaccity, udemy, coursera, online]

Your best bet is to break into a company that will teach you and you pick up the skills and the title and grow from there. I don't know how much you have gotten your feet wet with data engineering, but I would do a few projects and certificate just to familiarize yourself and boost portfolio (unless you know of someone that would give you internship or job right off the bat, if that is the case place the experience as the top priority)/

- Udacity has a data engineering nanodegree

- GCP offers this certificate through coursera

- Specialization in coursera

Also a good tip that would be helpful for your to break into your first job is applying for startups (cause once you get that first data engineering job it becomes a lot easier,) Generally, startups have a much lower barrier to entry and frankly need data engineers too. They will take a chance on you more than big companies. Once your there, you will be getting very hands on and learning fast and after a year or so you have that title and proven record and can jump somewhere else.

Happy to talk more but would love thoughts.