[FreeCoursesOnline.Me] A Cloud Guru - Google Certified Professional Data Engineer

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[FreeCoursesOnline.Me] A Cloud Guru - Google Certified Professional Data Engineer

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[FreeCoursesOnline.Me] A Cloud Guru - Google Certified Professional Data Engineer.torrent
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Uploaded on 16-04-2020 by our crawler pet called "Spidey".
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Description

Lynda and other Courses >>> https://www.freecoursesonline.me/
For Developer Tools & Apps >>> https://ftuapps.com/
Forum for discussion >>> https://1hack.us/



By : Tim Berry
Publisher : ACloud.Guru
Duration: 12.8 hours
Course Source : https://acloud.guru/learn/gcp-certified-professional-data-engineer

Learn how to design, build and operate powerful big data and machine learning solutions using Google Cloud Platform .

Description

Hello Cloud Gurus!

Data management, data analytics, machine learning and artificial intelligence are all hot topics. And who does these better than Google? Our Google Certified Professional Data Engineer course will help prepare you for the certification exam so you can take that next step in your Cloud career and demonstrate your proficiency in one of the most in-demand disciplines in the industry today.

The primary focus of this course is to prepare you for the GCP Professional Data Engineer certification exam. Along the way you’ll solidify your foundations in data engineering and machine learning, ensuring that by the end of the course you will be able to design and build data processing solutions, operationalize machine learning models and gain a working knowledge of relevant GCP data processing tools and technologies.

This course will teach you how to:

• Design, build and operationalize data solutions
• Process data streams in real-time
• Efficiently store and access data in the cloud
• Use the GCP pre-trained AI APIs (vision, speech and text)
• Train and operationalize ML models.

The Google Cloud Professional Data Engineer is for data scientists, solution architects, devops engineers and anyone wanting to move into machine learning and data engineering in the context of Google. Students will need to have some familiarity with the basics of GCP, such as: storage, compute and security; some basic coding skills (like Python); and a good understanding of databases. You do not need to have a background in data engineering or machine learning, but some experience with GCP is essential. This is an advanced certification and we strongly recommend that students take the Google Certified Associate Cloud Engineer exam before embarking on this course. However, anyone who is motivated and wants to understand how big data and machine learning is done on GCP will still find value with this course.

Keep being awesome, Cloud Gurus!

About Author

I'm a multi-skilled technologist with over 20 years of experience in the architecture and implementation of distributed enterprise systems. I've worked on large business-critical infrastructure overhauls, distributed virtualisation platforms and cloud migrations. I'm passionate about cloud-native technologies and automating all the things!



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Files in this torrent

FILENAMESIZE
0. Websites you may like/How you can help our Group!.txt208 B
01 Introduction/001 Welcome.mp430.2 MB
01 Introduction/002 About This Course.mp448.4 MB
01 Introduction/003 Course Audience and Prerequisites.mp412.3 MB
02 Data Processing Fundamentals/001 Data Processing Concepts.mp493.7 MB
02 Data Processing Fundamentals/002 Data Processing Pipelines.mp418.8 MB
03 Storage and Databases/001 Introduction to Data Storage in GCP.mp459.1 MB
03 Storage and Databases/002 Working with Data.mp416.2 MB
03 Storage and Databases/003 Cloud Storage.mp423.1 MB
03 Storage and Databases/003 GCS Documentation.txt39 B
03 Storage and Databases/003 GCS Pricing.txt41 B
03 Storage and Databases/004 GCS Access Control Lists (ACLs).txt73 B
03 Storage and Databases/004 GCS IAM Permissions.txt75 B
03 Storage and Databases/004 Service Accounts.mp414.9 MB
03 Storage and Databases/005 BigQuery Data Transfer Service.txt44 B
03 Storage and Databases/005 Cloud Storage Transfer Service.txt48 B
03 Storage and Databases/005 Data Transfer Services.mp48.9 MB
03 Storage and Databases/006 Cloud SQL Documentation.txt35 B
03 Storage and Databases/006 Cloud SQL.mp422.6 MB
03 Storage and Databases/006 Replicating from an external server.txt68 B
03 Storage and Databases/006 Requirements and tips for configuring replication.txt57 B
03 Storage and Databases/007 forumdb.sql65.5 KB
03 Storage and Databases/007 LAB Creating a Cloud SQL Instance and Loading Data.mp429.5 MB
03 Storage and Databases/008 Cloud Firestore Documentation.txt41 B
03 Storage and Databases/008 Cloud Firestore.mp423.6 MB
03 Storage and Databases/009 ANSI SQL best practices.txt57 B
03 Storage and Databases/009 CAP Theorem.txt42 B
03 Storage and Databases/009 Cloud Spanner Documentation.txt39 B
03 Storage and Databases/009 Cloud Spanner.mp428.3 MB
03 Storage and Databases/009 Distributed database quorums.txt61 B
03 Storage and Databases/009 Multi-regional best practices.txt76 B
03 Storage and Databases/009 Regional best practices.txt72 B
03 Storage and Databases/010 GCP Samples (C).txt59 B
03 Storage and Databases/010 GCP Samples (Go).txt54 B
03 Storage and Databases/010 GCP Samples (Java).txt57 B
03 Storage and Databases/010 GCP Samples (PHP).txt56 B
03 Storage and Databases/010 GCP Samples (Python).txt59 B
03 Storage and Databases/010 GCP Samples (Ruby).txt57 B
03 Storage and Databases/010 LAB Working with Cloud Spanner.mp421.8 MB
03 Storage and Databases/010 Node.txt45 B
03 Storage and Databases/010 spannerlab-schema.sql349 B
03 Storage and Databases/011 Cloud Memorystore Documentation.txt49 B
03 Storage and Databases/011 Cloud Memorystore.mp410.4 MB
03 Storage and Databases/012 LAB Working with Cloud Memorystore.mp436 MB
03 Storage and Databases/012 Redis-CLI Documentation.txt33 B
03 Storage and Databases/012 Retwis GitHub repo.txt46 B
03 Storage and Databases/013 Comparing Storage Options.mp414.7 MB
03 Storage and Databases/014 Exam Tips.mp46.9 MB
04 Big Data Ecosystem/001 MapReduce research paper.pdf186.2 KB
04 Big Data Ecosystem/001 MapReduce.mp449 MB
04 Big Data Ecosystem/002 Hadoop HDFS.mp422.8 MB
04 Big Data Ecosystem/003 Apache Pig.mp47.4 MB
04 Big Data Ecosystem/004 Apache Spark.mp430.2 MB
04 Big Data Ecosystem/005 Apache Kafka.mp417.1 MB
05 Real Time Messaging with PubSub/001 PubSub Concepts.mp451.3 MB
05 Real Time Messaging with PubSub/002 PubSub Basics.mp48.9 MB
05 Real Time Messaging with PubSub/003 LAB Working with Cloud PubSub.mp431.7 MB
05 Real Time Messaging with PubSub/004 bored.py1005 B
05 Real Time Messaging with PubSub/004 GCP Samples (C).txt59 B
05 Real Time Messaging with PubSub/004 GCP Samples (Go).txt54 B
05 Real Time Messaging with PubSub/004 GCP Samples (Java).txt57 B
05 Real Time Messaging with PubSub/004 GCP Samples (PHP).txt56 B
05 Real Time Messaging with PubSub/004 GCP Samples (Python).txt59 B
05 Real Time Messaging with PubSub/004 GCP Samples (Ruby).txt57 B
05 Real Time Messaging with PubSub/004 LAB Cloud PubSub Client Libraries.mp440.6 MB
05 Real Time Messaging with PubSub/004 Node.txt44 B
05 Real Time Messaging with PubSub/005 Advanced PubSub.mp417.3 MB
05 Real Time Messaging with PubSub/005 PubSub IAM Roles.txt67 B
05 Real Time Messaging with PubSub/005 PubSub Stackdriver Metrics.txt63 B
05 Real Time Messaging with PubSub/006 LAB Loosely Coupled Services with Cloud PubSub.mp435.8 MB
05 Real Time Messaging with PubSub/006 Source Code gen_thumbnail.Source Code gen_thumbnail2.3 KB
05 Real Time Messaging with PubSub/007 LAB Stream Data through Cloud PubSub to BigQuery.mp459.6 MB
05 Real Time Messaging with PubSub/007 MOCK_DATA.csv39.2 KB
05 Real Time Messaging with PubSub/007 transactions.py1.1 KB
05 Real Time Messaging with PubSub/008 Exam Tips.mp411 MB
06 Pipelines with Cloud Dataflow/001 Apache Beam overview.txt51 B
06 Pipelines with Cloud Dataflow/001 Apache Beam programming model.txt71 B
06 Pipelines with Cloud Dataflow/001 Dataflow Introduction.mp415.4 MB
06 Pipelines with Cloud Dataflow/002 Pipeline Lifecycle.mp416.1 MB
06 Pipelines with Cloud Dataflow/003 Dataflow Pipeline Concepts.mp415.2 MB
06 Pipelines with Cloud Dataflow/004 Advanced Dataflow Concepts.mp415.2 MB
06 Pipelines with Cloud Dataflow/004 Concepts.txt71 B
06 Pipelines with Cloud Dataflow/005 Dataflow Security and Access.mp417.1 MB
06 Pipelines with Cloud Dataflow/006 Deploying a pipeline.txt67 B
06 Pipelines with Cloud Dataflow/006 Using Dataflow.mp422.1 MB
06 Pipelines with Cloud Dataflow/007 Exam Tips.mp410.4 MB
06 Pipelines with Cloud Dataflow/008 Lab Commands.Lab Commands586 B
06 Pipelines with Cloud Dataflow/008 LAB Working with Cloud Dataflow.mp431.6 MB
06 Pipelines with Cloud Dataflow/009 Beam Programming Guide.txt57 B
06 Pipelines with Cloud Dataflow/009 Lab Code.Lab Code3.1 KB
06 Pipelines with Cloud Dataflow/009 Lab Commands.Lab Commands479 B
06 Pipelines with Cloud Dataflow/009 LAB Streaming Pipelines with Cloud Dataflow.mp460 MB
07 Managed Spark with Cloud Dataproc/001 Dataproc Overview.mp48.9 MB
07 Managed Spark with Cloud Dataproc/002 Dataproc Basics.mp48.3 MB
07 Managed Spark with Cloud Dataproc/003 Estimating Pi using the Monte Carlo method.txt53 B

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