Mar 03, 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.
Sep 24, 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.
Sep 06, 2018
Clear and informative videos introduced me to several new products. "cut & paste' Labs three starts. Lump first three into first, & two ML labs into one, & develop new ones that require students to write their own apps. The extra 'exploration time' on early labs was useless to me because did not have permission to set up a 'hello world' app. or access most of GCP options. Would be nice to provide lots of extra 'challenges' (w/tips, got FACE_DETECTION but never could view jpeg files)
автор: Anton A•
Sep 23, 2017
This is super important and interesting course. However, I'm not happy with pace of the course. Instructor's narrative is slow (I've found it can be heard at 1.25 speed without loosing a topic). Another "complain" is how topics are presented, author expresses too much personal experience on them. This is good and interesting, however, when you are on Coursera's deadline, you need to be material oriented. This is not my first course, so I can compare this course with other ones.
автор: Ingrid J•
Nov 10, 2018
I really enjoy the instructor's way of explaining things and the content was basic but clear. I found the course a bit basic for my skillset so I would like to have some challenging alternative in the labs. More hands on. Example: instead of telling me the command line to import a file into Cloud storage, provide an instruction such as: using gutil upload the csv file into Cloud Storage. (hide the solution and allow me to see the solution if I want/need to)
автор: Evan P•
Dec 27, 2017
"GCP Big Data and Machine Learning Fundamentals" provides a good overview of the GCP ecosystem and pushes a compelling case for adopting their "no-ops" managed services. The course provides labs that will familiarize you with each component of the ecosystem but only slightly beyond the extent that it gives you a feel for the "administrative" steps of using GCP. It defers to Google's Data Engineering courses for more depth and implementation practice.
автор: Mike H•
Sep 22, 2018
I wish the labs were more polished and that they built on each other (i.e., that Lab 3b doesn't start with doing everything in Lab 3a all over again). It can be tedious to redo everything. The buggy scoring module connecting Qwiklab and Coursera is a distraction. The content of the videos is very helpful in getting an overview of the GCP platform which can be very intimidating at first with all of the different brands to keep track of.
автор: Christian B•
Jan 12, 2018
Content is very good, but as a non native english, it's very difficult to listen to the speaker. He has a very strong indian accent. It's something any speaker should work on before recording such videos.
Second, it would have been more professional to show better preparation, avoiding repeating himself. Sometimes the best is to reshoot some missed parts. It's an training course !
And please, stop saying the word "basically"...
автор: MAYANK G•
May 05, 2018
Thanks to this course that I got to know, how GCP reduces the time and ops required to do advanced data analytics and build scalable Data Science products. Detailed differences between the same class of products GCP has to offer such as (Cloud SQL, BigTable, DataStore etc.) can add cherry on top of this course. Also, case studies in class with some practical assignments can be a good addition to the course.
автор: Padma E•
Mar 23, 2020
it is good course but some of the instructions for labs are not clear. Hope this would be a credited course. I took this course for two reasons. One is to get paid for the work have been doing as unofficial consultants to various organizations online and to learn and improve my knowledge on Big Data and ML. Hope this course would help me to explore more opportunities at Google and other organizations
автор: Jianhong X•
Jan 12, 2019
thank you for hosting these lectures where I benefit a lot. It could be better if
1. combine several lab session into one and avoid the waiting for opening the cloud lab. (5 min for each);
2. It might be more helpful to have more (graded/ with feedback) practice on Jupyter notes. The course seems designed more about building concepts rather than helping students pick up the skills.
автор: Konstantinos S•
Jan 07, 2019
Overall a very good course. I would have liked a bit less "google is great" stuff and a bit more depth into their products, including an equivalence with AWS and Azure services. The labs were very interesting but some of them were repeated and a bit basic in the graded part (for instance the ML API lab tests whether I can clone a repo using a web interface and full instructions).
автор: Eric L V•
Sep 23, 2019
The course was a big light in scope. The final lab also has a problem in that if you click on the AutoML bolt-on application URL (from the labs START/END LAB page), you loose your credentials page and ability to finish the lab. The verbiage around starting up AutoML need to be much clearer -- e.g. 'copy the AutoML URL here, into your incognito browser'.
автор: stefano d p•
Dec 30, 2017
materials could be updated to be in line with the labs. Moreover it would be nice to cut moments where the speaker got lost during the videos in order not to lose time (many times there were 20 sec of silence).
Other than that the course is great. It would be nice yo have more info about the certification (mainly about the structure of the exam)
автор: vinsent p•
Aug 08, 2017
The realtime examples of the cine industry image processing was really good to see the power of GCP.
Some more in-depth example of query the cloud storage, and G C function should have added weight-age to the course, other wise the instruction are good to start the Google cloud.
More examples of using the google CLI should have been added.
автор: Duncan T•
May 26, 2018
Better than I expected. I thought it would just be a massive advertisement, but there was actually some good and interesting content. I guess it helps when the api's your are promoting are really cool. The labs were helpful, but separate steps of lab 4 should have been combined. It took a long time for datalab to set up for a 15 min lab.
автор: Sonila K•
Aug 14, 2018
Bumping the score by a point due to great tech/customer support.
The lab instructions could be clearer and the real time update of scores is not working for few of the labs that needs to be corrected. Content was good.
автор: Pradeep D M•
Dec 05, 2018
The Tutor is very knowledgeable and provides a good mix of examples along with each chapter. However, the exercises are quite repetitive and seems like the gap between exercises and the lectures sometimes is too long. The user experience could be improved by using the same project across similar lab exercises with reduced setup time.
автор: Jingjing W•
Feb 23, 2020
This class has the fundamentals of GCP. It is pretty easy and all you need to do is follow the lab instruction and you can get the basic idea of using the google cloud services. However, there is no requirement for coding (mostly just copying the code). It is not recommended for advanced programmers who already know the services.
Jul 25, 2018
It was a decent course, but in my opinion focused too heavily on delivering everything via video lecture with very little supplemental material (other than what's already available from Google Cloud's docs). I would have liked to see some challenges as well, rather than just labs that required you to "fill in the blanks"
автор: Felipe H d A B•
Apr 26, 2020
Great course, gives a great overview of the resources, some labs are really good but the machine learning part is not that well, you just learn a bunch of stuff but actually don't practice it that much so it's actually just an overview which will you give more knowledge about the services but not actual experience.
автор: Berry J•
Sep 03, 2018
Machine learning concepts are at a high level for a beginner as all the concepts used in lab are new. I was not able to 100% understand the code but just understood what can be done through Google Machine Learning support. In the lab we just ran the commands but couldn't understand the terminology or logic used.
автор: Mananai S•
Dec 31, 2018
A good introduction to GCP. The course covers tools you need to do big data and ML. Instructor is an expert in this field. The labs are practical help you practice how to do the real work. I have experience in ETL, both SQL and NoSQL . Now, I am convinced that Cloud solution is better than the traditional way
автор: Trilok K•
Apr 24, 2017
It's a short but good course. Good instructions and delivery. Good introduction to Big Data and ML on GCP. Would have liked more assignments as a formal requirement to complete the course. The codelabs are disconnected from the course. Glad to know other courses in the specialization are under development.
автор: Claudia C•
Apr 15, 2020
The course was very very nice, with practical examples and good explanations, though the beginning can be improved for someone that did not work much with many services from GCP. Other than that, it is easy to go through, to get your skills from hands on examples and start new endeavors using GCP.
автор: Carl N•
Apr 11, 2020
It was a good course for learning all the many Google Cloud Platform products and capabilities. As an introductory course, it doesn't provide enough depth to become proficient in a skill. It's exposures you to the highlight workflows, processes, and use cases of the various products and tools.
автор: Ruben S C•
Apr 29, 2018
Me parece muy bueno el curso, pero por el momento hay algunos cambios en la plataforma practica, son detalles pero al momento de seguir las instrucciones, cambian algunos menús, se entiende que es por la constante actualizaciones de la plataforma web de GCP. (esto hace perder un poco de tiempo).