Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Language
English
Taught by
Loony Corn
Rating
Course Overview
The Google Cloud for ML with TensorFlow, Big Data with Managed Hadoop
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)
Course Content
- 21 section(s)
- 226 lecture(s)
- Section 1 You, This Course and Us
- Section 2 Introduction
- Section 3 Compute
- Section 4 Storage
- Section 5 Cloud SQL, Cloud Spanner ~ OLTP ~ RDBMS
- Section 6 Hadoop Pre-reqs and Context
- Section 7 BigTable ~ HBase = Columnar Store
- Section 8 Datastore ~ Document Database
- Section 9 BigQuery ~ Hive ~ OLAP
- Section 10 Dataflow ~ Apache Beam
- Section 11 Dataproc ~ Managed Hadoop
- Section 12 Pub/Sub for Streaming
- Section 13 Datalab ~ Jupyter
- Section 14 TensorFlow and Machine Learning
- Section 15 Regression in TensorFlow
- Section 16 Vision, Translate, NLP and Speech: Trained ML APIs
- Section 17 Virtual Machines and Images
- Section 18 VPCs and Interconnecting Networks
- Section 19 Managed Instance Groups and Load Balancing
- Section 20 Ops and Security
- Section 21 Appendix: Hadoop Ecosystem
What You’ll 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
Skills covered in this course
Reviews
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FFeng Cai
very dry materials.
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SShaohua Qu
The video content is rich, and learnt a lot details of GCP. From pass the exam perspective I'm not sure all the content is closely relevant. And, I'm not able to fully get some points due to the accent...
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MManmoyuri Devi
Explanations are not very good. The presenter is mostly just reading through the slides. The labs are very difficult to follow at times since the presenter happens to be in a hurry. Also, Q/A are not answered. The presenter is referring to scripts without telling where to get them.
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JJoy B
This Course is really Great.. This gives a meticulous focus on the topics with a sincere attitude.. The only reason I am putting 4.5 (not 5) is that I am not sure if this course is being updated per the Real Exam updates as of 2019.
