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12,294 Bewertungen
2,204 Bewertungen

Über den Kurs

This 2-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. At the end of this course, participants will be able to: • Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform • Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform • Employ BigQuery and Cloud Datalab to carry out interactive data analysis • Choose between Cloud SQL, BigTable and Datastore • Train and use a neural network using TensorFlow • Choose between different data processing products on the Google Cloud Platform Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following: • A common query language such as SQL • Extract, transform, load activities • Data modeling • Machine learning and/or statistics • Programming in Python Google Account Notes: • Google services are currently unavailable in China. New! CERTIFICATE COMPLETION CHALLENGE to unlock benefits from Coursera and Google Cloud Enroll and complete Cloud Engineering with Google Cloud or Cloud Architecture with Google Cloud Professional Certificate or Data Engineering with Google Cloud Professional Certificate before November 8, 2020 to receive the following benefits; => Google Cloud t-shirt, for the first 1,000 eligible learners to complete. While supplies last. > Exclusive access to Big => Interview ($950 value) and career coaching => 30 days free access to Qwiklabs ($50 value) to earn Google Cloud recognized skill badges by completing challenge quests...

Top-Bewertungen

VS
2. März 2019

Overall a good curated course to help understand the GCP offerings and high level architecture of how their offerings fit in the current landscape. Easy to follow along as this was fundamental course.

AD
23. Sep. 2019

This course really helped me in understanding exactly 'How the Big data and Machine learning can be used in Cloud' and 'The ease to use it'. Thank you for summing all the fundamentals in this course.

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26 - 50 von 2,177 Bewertungen für Google Cloud Platform Big Data and Machine Learning Fundamentals

von Jake

3. Juni 2018

I enjoyed the course and the way labs are done is excellent. 3 of the labs were just spinning up and running the same notebook, I think this was a lost opportunity.

von Gerardo N

21. Aug. 2020

The course is great, but some of the labs are not well maintained, which can be very frustrating.

von Mohan K

14. Juli 2018

The environment is not very stable and performance is not very great

von Linda F L

5. Okt. 2020

The labs were horrible. I never knew if they would run or not.

von Kushal J

1. Nov. 2018

Great content, let down by technical issues using Qwiklabs

von Hanumantha R V

26. März 2019

Very Basic course.. But helpful to get started with GCP

von dpeif d

14. Nov. 2018

Some labs are very repetitive and feel useless

von Sandhya A P

18. Juli 2018

Labs have a lot of errors with grading

von Tamás-Marosi P

20. Sep. 2017

Just from the lessons the quizes questions were hardly solvable. Of course with the review video, where the answers were publicated, reaching the 100% was challangless.

The Labs were correct, but there were some bugst and errors, when the labs steps say something but with these steps the environment throw errors. Again there were videos where the presenter shows the steps, which were more or less the same as the labs steps, but with these plus steps the environment worked without errors.

In the labs steps there were fill out type questions, but I wasn't able to fill them out. It would be great if these questions will be implemented into the quizes.

von Celia M

3. Jan. 2020

There is valuable information in the course and some good exercises, but they are hidden among many information which is not so useful. In overall it is an entry class to use the technology, but many customers already know this sort of things because they tested our products or the features we comment here are similar to features of other vendors' products. Their reaction when they are presented the technology for the first time is: "Thank you. My questions and issues are quite specific and not reflected here".

von Paul C

10. Dez. 2018

had to contact customer service for qwiklabs twice due to it bugging out & becoming unusable.

Also if you go outside of the "Script" & miss one step in the instructions for an exercise, it becomes really hard to figure out what it was that you did wrong.

Lastly this is definately not a "compressed course". It could be completed it one week if you literally dedicated a whole week of time to it but for those of us who are doing this part time & actually want to absorb the content, expect to plan for 2-3 weeks

von Lourdes R

19. Apr. 2020

Steps missing in the labs. The documentation cannot be downloaded from just one click. The instructions in the lab miss some steps. It would help to have a diagram with the steps, incomes outcomes and things to consider to avoid errors.

von Vinod S K

6. Mai 2020

The contents covered are good. However, the labs had many issues. I spent more time debugging and talking to tech support than I spent doing the lab exercises.

Overall, I feel not the best utilization of my time.

von Jón A T

3. Juni 2020

Superficial. Little learning occurred. Basically a product presentation.

von jiawei

20. Sep. 2020

many labs doesn't work

von Felix E

25. Okt. 2017

TL;DR: I sadly have to say that this course was absolutely not worth the time. I would recommend anyone looking to get started with Google Cloud to just go through the examples in the Google Code Labs, since you'll get about the same information in a much smaller timeframe.

I can't recommend this course to anyone for the following reasons:

(1) For the most part, it feels more like a Google self promotion than an educational class.

(2) Most of the content in this course is based on the exercises from Google Codelabs (or rather, they link you to the exercise on the google platform), which themselves are all right. The video lectures, however, rarely add anything of value, definitely not with respect to the amount of time they take to complete. Overall, a rather low "production value"/"-quality" compared to other courses in Coursera.

(3) The course attempts to showcase how easy some complicated tasks are in Google Cloud Engine. However, you're just given the task to execute long and rather complicated scripts that Google has provided just for this course. Those scripts and what happens in the background is not explained in depth, instead it's often emphasized how easy everything is with GCE. No mentions of what to do when you DON'T have a huge amount of code already provided by Google.

(4) The course content is not adapted well for the Coursera format. Around 50 chapters, partly only with 15 second videos, so you have to scroll a lot and it's hard to see how content was intended to be grouped. The tests/mutliple choice exams are also very badly done, feels like they were made with the lowest amount of effort possible.

von Ekaterina P

2. Juni 2018

Very raw. Have to restart labs several times, because sometimes they just do not work. Just that (like there should be a button(exists in video), but you can't find it). Very frustrating. Not to mention that for your own money they are advertising google-cloud to you... :)

Google cloud itself is buggy for now...

On technical side of the course: it is made to maximize the number of sections and videos. Just like some ... code that maximizes lines of code. Yes, it's like 10 second videos in the separate section. Many of them. I like short 3-10 min videos, but 10 second ones? Labs that officially take 1h, but if google cloud is not bugging it is 15-30 min. Labs where instructions tell you to stop half way through, because the rest would be in the next lab!!! (so you would have to redo those steps, yeah). Probably maximizing the number of labs too... Lots of frustration!

von Nicholas C

2. Juli 2019

This course doesn't introduce you to the concepts; more so it is an advertisement for Google Cloud Products. The labs don't explain how things work, they are just naive click-along activities.

von Zhe S

27. Sep. 2018

Very bad experience with labs facilited by Qwiklabs. The scored cannot be saved by Qwiklabs correctly. I have to retried several times and upload the screenshot to manually update my score!

von Sainath R

2. März 2019

Some lab exercises have issue and the score doesn't get updated even though the all steps are completed

von Ivan R

24. Dez. 2018

most options don't match with current menu

von wenhui z

25. Feb. 2018

The lab is outdated

von Nikhil M

16. Juli 2020

In this course, I learned How to use the Google cloud platform(GCP) and it's tools like BigQuery, Cloud Storage, Vision, Dataproc, Pub/Sub, Dataflow, compute engine, etc.

In GCP, we can generate the instance of Virtual Machine(VM). It's a serverless platform (Google has it's own data centers). We can develop a complete software through GCP.

IN GCP, we can build custom models. It is very handy to operate for BigData. The Data in GB, TB, or PB can be processed in seconds or minutes on GCP.

Also, I deployed the ML model for Classifying Images with Pre-built ML Models using Cloud Vision API and AutoML.

In this model, we classified the Images of clouds in three categories., viz cirrus, cumulonimbus, and cumulus.

The cool features of AutoML and Vision API-

-We don't have to write code for building the machine learning(ML) model.

-AutoML decides the dataset splits for training and testing.

-If you are working with a dataset that isn't already labeled, AutoML Vision provides an in-house human labeling service.

- We have to just evaluate the model by adjusting the Confidence threshold and the confusion matrix.

Sometimes the training time will be more because of large datasets, node training time as well as infrastructure set up and tear down.

Though it is cost-efficient because you have to pay for the memory you use, The time processing takes place(for Training the nodes in ML), etc.

The bottom line is GCP offers IaaS (Infrastructure as a Service) in the form of Google Compute Engine, and it offers Paas (Platform as a Service) in the form of Google App Engine. As for FaaS (Function as a Service), GCP offers it in the form of Google Cloud Functions.

von Aditya D

22. Juli 2020

I am fascinated to learn how Google Cloud successfully builds applications that use our big data and machine learning products. This course helped me to understand real-world data and ML challenges and gave practical hands-on expertise in solving those challenges using Google Cloud Qwiklabs.What were the challenges faced?1. Migrating existing big data workloads to an environment where we can effectively analyze all of your data, interactively analyzing large datasets using BigQuery2. Building scalable pipelines that can handle streaming data, so that businesses can make data-driven decisions more quickly using Cloud Pub/Sub and Cloud DataFlow3. Building machine learning models(recommendation, prediction and classify images) so that we are able to make predictive forward-looking actions using our data using Cloud SQL, Spark, VisionAPI and Cloud AutoML

von Ulises L

27. Sep. 2019

Valuable overview of central big data topics and how they are supported by Google Cloud Platform. Labs are clear and well thought out, but I did have some struggles with a minor misalignment between what I saw upon "open console" - (a sign-in window), and what the lab expected me to see (a "choose account" window). When I viewed the qwiklabs overview video again, it then became clear to me that I needed to simply go ahead and sign in with the credentials provided by the lab. It might be appropriate to update the lab instructions accordingly.