Google Cloud Professional Data Engineer Course [2019 Update] by Samuel Lee

Udemy course Google Cloud Professional Data Engineer Course [2019 Update] by Samuel Lee

Google Cloud Professional Data Engineer Course [2019 Update] is the best Udemy course on the market. With this offer they will be able to greatly improve their knowledge and become more competitive within the IT & Software category. Therefore, if you are looking to improve your IT & Software skills we recommend that you download Google Cloud Professional Data Engineer Course [2019 Update] udemy course.

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Course data:

  • Author: Samuel Lee
  • Course rating: 4.3
  • Category: IT & Software
  • Modality: Online
  • Status: Available
  • Idiom: English

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Abouth Samuel Lee

Hi I am Sam! A Big Data Engineer, Cloud Engineer and Machine Learning/AI Enthusiast. For my day to day activities I like to first start my day with a cup of Coffee then start solving real world problems mainly to do with Big Data technologies (Different Cloud Technologies mixed with Open Source systems such as hadoop vendors) and Websites (Backend APIs and Front End presentation).

Google Cloud Professional Data Engineer Course [2019 Update]

What the udemy Google Cloud Professional Data Engineer Course [2019 Update] course teaches?

What you’ll learn Understand major components of GCP, why and when to use its Products Connect into GCP VMs using SSH Build a dataset using BigQuery Repeat command from BigQuery in Datalab and Plot a Graph Dashboarding in Datastudio Machine Learning and AI Fundamentals Hadoop Application of GCP Products in Real World Applications

Take this course to prepare for the GCP Data Engineers Exam. Updated to reflect latest exam content.

More information about the course Google Cloud Professional Data Engineer Course [2019 Update]

[UPDATED CONTENT 2019 Exam] Storage Solutions OLAP vs OLTP databases Consistency concepts. Transactional consistency for various data storage solutions. Cloud Storage Gsutil command line interface. Datastore Datastore indexing – what is it, how to update, upload. BigQuery Update of BigQuery practicals including authorised views in the new BQ UI. Concepts of temporary tables. Types of schemas BQ accepts. BigTable BigTable fit for purpose of time-series data. Cbt command line interface for BigTable. BigTable consistency concepts and highly available configuration. Dataflow Deploying dataflow jobs and what’s running in the background. Dataflow job monitoring through console -> Cloud Dataflow Monitoring Interface and also gcloud dataflow commands. Updating a dataflow streaming job on the fly. Logging of Cloud Dataflow jobs. Cloud Dataflow Practical – Running job locally and using Dataflow Service Hadoop & Dataproc Apache Spark jobs Stackdriver Export logs to BigQuery for further analysis, why and how. Machine Learning Solutions – New Section Introduction of new GCP ML products and open source products such as Cloud Machine Learning Engine, BigQuery ML, Kubeflow & Spark ML Cloud AutoML -> AutoML Vision, AutoML Vision Edge Dialogflow – GCP’s Chatbot builder Concept of edge computing and distributed computing Google cloud’s TPU (Tensor Processing Unit) Common terms in Machine Learning terminology such as features, labels, models, linear and logistic regression, classification, clustering/networks and supervised/unsupervised learning. Migration into GCP – New Section How to migrate data into GCP – Transfer Appliance & Storage Transfer Service Dataprep – New Section What is Dataprep? Dataprep practical section, runs Dataflow job in background – nice interface for non-coders Security on GCP – New Section Cloud security best practices Securely interacting with Cloud Storage Penetration testing Bastion/Jumphost Encryption Data loss prevention api Live migration Cloud Composer – New Section What is cloud composer? Hi I’m Sam, a big data engineer, full stack web developer and machine learning/AI Enthusiast teaching you GCP in the most efficient and down to earth approach . I will teach you the core components of GCP required to pass the data engineers exam using a real world applications approach . All the practicals in this course show you techniques used by big data engineers on the GCP . Course is streamlined to aim to get you to pass the GCP Data Engineers Certification . Therefore, it is the most time efficient course to learn about GCP if you want to have a good understanding of GCP’s products and have the intention of becoming a certified data engineer in the future. The course is streamlined to under 5 hours! Learn all about GCP over a weekend or in a day ! Infrastructure solutions will be presented for various use cases as you learn the most when solving real problems ! Theory and Practicals will be placed to aim to pass the Data Engineers Exam with the shortest amount of time. In the exam most questions will be targeted on the why and not the how. For example you will be very hard pressed to find a question that asks you to choose the correct code snippet out of the 3 code snippets etc. Student Feedback: Hi Samuel. Hope this finds you well. I passed the GCP data engineering exam last week and just want to thank you for your Udemy course that summarises the exam materials so well! Have a good week ahead! The course is helpful for my preparation of Google Data Engineering Certification Exam. It also gives a good and brief overview of GCP products that is lacking in other courses. The knowledge gained from this course can be applied to using GCP in data scientist and data engineering work. I had tried coursera courses from google. It’s too longer and has lots of marketing pitches. I like your approach. You should create another course like this for AWS or GCP architect. Course is split up into sections as below: Introduc…

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