GCP: Complete Google Data Engineer and Cloud Architect Guide (Udemy.com)
The Google Cloud for ML with TensorFlow, Big Data with Managed Hadoop
Created by: Loony Corn
Last updated July 2018
What you will learn
- Deploy Managed Hadoop apps on the Google Cloud
- Build deep learning models on the cloud using TensorFlow
- Make informed decisions about Containers, VMs and AppEngine
- Use big data technologies such as BigTable, Dataflow, Apache Beam and Pub/Sub
How it compares
Against the other 848 rated Udemy courses in IT Certifications on CourseDuck:
- Rating4.0 out of 5higher than 3% of them
- Reviews7,369#61 of 849 by number of reviews
- Length27.9 hourslonger than 92% of them
- Last updatedJuly 2018earlier than 96% of them
Course Description
This course is a really comprehensive guide to the Google Cloud Platform - it has ~25 hours of content and ~60 demos.
The Google Cloud Platform is not currently the most popular cloud offering out there - that's AWS of course - but it is possibly the best cloud offering for high-end machine learning applications. That's because TensorFlow, the super-popular deep learning technology is also from Google.
What's Included:
- Compute and Storage - AppEngine, Container Enginer (aka Kubernetes) and Compute Engine
- Big Data and Managed Hadoop - Dataproc, Dataflow, BigTable, BigQuery, Pub/Sub
- TensorFlow on the Cloud - what neural networks and deep learning really are, how neurons work and how neural networks are trained.
- DevOps stuff - StackDriver logging, monitoring, cloud deployment manager
- Security - Identity and Access Management, Identity-Aware proxying, OAuth, API Keys, service accounts
- Networking - Virtual Private Clouds, shared VPCs, Load balancing at the network, transport and HTTP layer; VPN, Cloud Interconnect and CDN Interconnect
- Hadoop Foundations: A quick look at the open-source cousins (Hadoop, Spark, Pig, Hive and HBase)
Instructor Details
- 4.0 Rating
7,369 Reviews
Loony Corn
Loonycorn is us, Janani Ravi and Vitthal Srinivasan. Between us, we have studied at Stanford, been admitted to IIM Ahmedabad and have spent years working in tech, in the Bay Area, New York, Singapore and Bangalore.
Janani: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft
Vitthal: Also Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too
We think we might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why we are so excited to be here on Udemy!
We hope you will try our offerings, and think you'll like them :-)
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Reviews
By André Luis Andrade Machado on 11/6/2023
The course content is well presented, and is sufficient for a GCP introduction focused a little bit more on tools for Data Engineering. Unfortunately, the content is a little bit outdated, which can make following the labs harder, on in some scenarios, impossible. But despite that, it continues to be a great conceptual introduction to GCP.
By Jen-Li Chen on 11/11/2021
matericals was mostly outdated, nobody answered students' questions. No power point provided for taking notes.
By Den on 9/30/2020
+Useful broad overview if you are completely new to GCP -Course material is outdated and some key new capabilities are not covered -No instructor support so don’t expect to get answers to any of your questions -Due to variety of instructors, lecture vary in style and quality -Too many bullet point slides and transitions making note-taking a pain
By Keith Pearson on 12/17/2019
This was a relatively good match for my knowledge level and previous Unix/Linux experience. The student needs to have some background to pick up on this course. Beginners won't understand it. Due to the age of this course (produced in 2017) some things in GCP and other areas have changed with age and updates making it harder to get some of the labs to work. Overall it covers concepts well on a wide variety of topics and the labs reinforce the lectures quite well.
By Venkataraman Nagarathnam on 5/21/2018
Sitting over a 230 sessions for a newbie like me, especially with workloads in my profession requires the presenter to be really really engaging. This is what this course was exactly about. I learnt a world of technologies which kept me constantly engaged. With the sessions broken into 10 minutes cycle and alternating with lab exercises made this absolutely interesting to learn. I really appreciate all the instructors for the great efforts in racking up such a world of knowledge in this course. Their efforts to compile such a valuable course is seen all throughout. Kudos to all of you instructors ! SALUTE !
By Suman Guha on 5/9/2018
You guys have done an extraordinary job in teaching the content and providing context to what is relevant. However, one suggestion would be if you can introduce a section providing a quick synopsis of content break down between Data Analyst and Cloud SA certification that would be great. In any case, this would be added advantage but you folks have done tremendous job, I am AWS Certified SA professional, Red Hatter and working in Cloud domain and have strong desire to finish GCP certifications, I am big time google fan. The course gives great opportunity of ex-Google engineer's clarity of thought on how to proceed GCP. Great Job!
By Sanjeev Garikapati on 3/15/2018
The course is well organized and probably the only course which covers the aspects of both Data engineering and architecture. I cleared both the exams . Though this course is not a comprehensive resource for clearing the exams, it establishes a very good base for one to build upon. I like the delivery and passion of the instructors in teaching.
By Piotr Kosmowski on 12/29/2017
I'm a person who passed GCP Architect exam and for me this course is just an introduction to the certification preparation for the Architect as well as for the Data Engineer. It's mostly a walkthrough of the official documentation in a pill and the labs are walkthrough of the official Codelabs. Mostly I'm missing here some architecture application cases, case studies for the app migration, building hybrid systems or debugging issues using GCP tools. However I find that there are some summarization moments that makes this course worth to invest some time.
By Bhagyashree Singh on 11/25/2017
This GCP course is really great! It is perhaps the most exhaustive one since the creators did not shy away from putting topics such as Tensorflow ML in extensive detail to cover cloud engineer exam as well. From architects point of view also, content is very good. Labs based on N/W and VPCs are quite good actually! It's content is as good as you can get on acloudguru for AWS or Linux Academy for GCP. I can say that because for my Google Cloud Data Engineer exam, I am subscribed to Linux Academy. This is a very high quality course.
By David Saleh on 10/8/2017
The course is great and there are lots of learning, probably need to re-take it again! but again, I think this is one of the best courses with great instructors. I just passed my Cloud Architect certificate, I believe this course was a major contributor to my success. will re-study data engineer section again before go to exam.
Quality Score
Overall Score : 80 / 100












