Google Cloud Professional Data Engineer Course [2019 Update]

Category: Tutorial


Posted on 2022-01-07, by raymanhero.

Description

17631c31-b1b1-487d-ba02-e4b243064079.png
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 53 lectures (4h 40m) | Size: 1.18 GB


==

Take this course to prepare for the GCP Data Eeers Exam.


Updated to reflect latest exam content.

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

Basic understanding of Relational Databases and NoSQL

SQL Basics

Some understanding of Virtual Machines will be beneficial

Desire to Learn!

[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 -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 Ee, 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 teology such as features, labels, models, linear and logistic regression, classification, clusterietworks 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 eeer, 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 eeers exam using a real world applications approach. All the practicals in this course show you techniques used by big data eeers on the GCP.

Course is streamlined to aim to get you to pass the GCP Data Eeers Certification. Therefore, it is the most 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 eeer 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 Eeers Exam with the shortest amount of . 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 eeering 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 Eeering 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 eeering 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:

Introduction - Explore questions, Why Cloud, Why GCP, main differentiators of GCP/main selling points, setup your free GCP account

Compute Ee - Overview of compute ee and pricing innovations, zones & regions, various machine types and practical to spin up VMs and access them via SSH, Mac and Windows supported

Storage Solutions - Overview of GCP's data storage solutions including Cloud Storage, Cloud Datastore, Cloud Spanner, Cloud SQL, BigQuery & BigTable. We will compare these storage solutions with each other and explain use cases where one storage solution will excel over another.

IAM & Billing - Different member types, roles and permissions, resource hierarchy and billing process

BigQuery - BigQuery Pricing structure, tips for reducing processing cost, Partitioned & Wildcard tables, Authorised views, Practicals in BigQuery using standard SQL

Cloud Datalab - How to use Cloud Datalab in a practical with a live feed from BigQuery to explore the dataset.

Cloud Pub/Sub - Pub/Sub concepts and its components especially decoupling and the uses of Pub/Sub

Hadoop & Dataproc - Overview of hadoop and major components which will be tested in the exam

Cloud Dataflow - What is dataflow, the dataflow model, how and why its used with relation to other GCP Products

Stackdriver - Stackdriver functions such as debugging, error reporting, monitoring, alerting, tracing and logging.

Tensorflow & AI - Brief overview of machine learning and neural networks, play with neural networks with a playground and understand GCP's AI products and APIs

Case Study - Finally, Put your new learnt GCP knowledge to use in a real world application business case. Similar case studies will be present in the exams.

For anyone who wants to learn about Google Cloud

For anyone who wants to be a Certified Google Cloud Data Eeer

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