Udemy

Hands on Google cloud platform(GCP) - Data Engineer

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  • 947 Students
  • Updated 3/2018
3.3
(193 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
4 Hour(s) 26 Minute(s)
Language
English
Taught by
Notez (Rent a Mind)
Rating
3.3
(193 Ratings)

Course Overview

Hands on Google cloud platform(GCP) - Data Engineer

Data Engineer Certification

This course is exclusively designed by NoTEZ to teach about GCP in most simplest way possible.


Students who enrolled for our previous courses on GCP had requested more in the series and hence this course is live.


If you havn't enrolled for our Other courses, enroll today n start exploring more.


This course is designed to give idea about Google' s data engineer certification But Not limited to just that.


This course will give you indepth practical knowledge on various components of GCP.


Enroll today & explore more

Course Overview


Module 1- Introduction


All about Google certification, Overview –Data Engineer Certification, What is and why to use CLOUD?


Module 2 - Hands on GCP


Labs


Module 3 –Hadoop


Introduction to,Hadoop, Hadoop-bigger picture, Hadoop- In detail, HIVE, HBASE,PIG


Module 4- Compute


Introduction to Computing, Google compute engine(GCE), Preemptible Virtual Machine, Google APP engine (G A E), Google container engine ,Kubernetes ( GKE),Comparison,Labs


Module 5- Storage


Introduction, Cloud Storage, BIGQUERY, Data Store, More on cloud storage, Working with cloud storage, Transfer service, Cloud SQL, Cloud SQL – PROXY, Cloud Spanner, Hot Spotting, Data Types, Transactions , Staleness, Labs


Module 6-Big Table


Big Table Introduction, Columnar store, Denormalized Storage, CRUD Operations, Column families, Choice of BigTable


Module 7-Datalab


Module 8-Pub/Sub


Module 9- Dataflow


Module 10-BigQuery


BigQuery Data Model, Querying & Viewing,Labs


Module 11-Machine Learning & Tensorflow


Introduction to Machine Learning, Typical usage of Mechine Learning, Types,


The Mechine Learning block diagram, Deep learning & Neural Networks, Labels, Understanding Tenser Flow, Computational Graphs, Tensors, Linear regression , Placeholders & variables,


Image processing in Tensor Flow, Image as tensors, M-NIST – Introduction, K-nearest neighbors Algorithm, L1 distance, Steps in K- nearest neighbour implementation, Neural Networks in Real Time, Learning regression and learning XOR


Linear Regression, Gradient descent, Logistic Regression, Logit, Activation function,Softmax, Cost function -Cross entropy,Labs


Module 12-Operation & Security


Stack driver, Stack driver Logging, Cloud Deployment Manager, Cloud Endpoints, Cloud IAM ,API keys, Cloud IAM- Extended, Labs,


Course Content

  • 12 section(s)
  • 54 lecture(s)
  • Section 1 Introduction
  • Section 2 Dive into practicals
  • Section 3 The Mighty 'HADOOP'
  • Section 4 Cloud compute engine
  • Section 5 Let's Explore Storage
  • Section 6 Big Table- columnar store
  • Section 7 Cloud Datalab
  • Section 8 PUB/SUB
  • Section 9 Dataflow
  • Section 10 BigQuery
  • Section 11 Machine Learning & Tensorflow
  • Section 12 Add on: operations & security

What You’ll Learn

  • Understand major components of GCP, Understand Machine learning fundamentals, Get introduced to BigQuery, Know how to use tensorflow on cloud, Learn about Hadoop and its cloud Counter parts, Get basics set to be certified


Reviews

  • A
    Anand Prakash
    2.5

    very basic and outdated course

  • J
    Jesus Humberto Rodriguez Banda
    5.0

    todo bien

  • l
    lydia ray
    3.0

    Good stuffs: storage explanations and the labs. Need to improve: a number of typo or miss-spelling; perhaps better to be less sentences more key words in the presentation.

  • A
    Anton Royce
    3.5

    all good

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