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A Cloud Guru | Google Certified Professional Data Engineer [FCO]
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A Cloud Guru | Google Certified Professional Data Engineer [FCO] (Size: 2.6 GB)
| 0. (1Hack.Us) Premium Tutorials-Guides-Articles & Community based Forum.url | 409.6 B | ||
| 001 AI at Google.txt | 0 B | ||
| 001 Apache Beam overview.txt | 0 B | ||
| 001 Apache Beam programming model.txt | 102.4 B | ||
| 001 BigQuery Basics.mp4 | 15.3 MB | ||
| 001 BigQuery documentation - working with datasets.txt | 102.4 B | ||
| 001 BigQuery main page.txt | 0 B | ||
| 001 Bigtable Concepts.mp4 | 13.9 MB | ||
| 001 Cloud AI Cloud APIs.mp4 | 12.6 MB | ||
| 001 Cloud Composer Overview.mp4 | 15.3 MB | ||
| 001 Cloud Datalab docs.txt | 0 B | ||
| 001 Colab tutorial.txt | 0 B | ||
| 001 Data Processing Concepts.mp4 | 93.7 MB | ||
| 001 Dataflow Introduction.mp4 | 15.4 MB | ||
| 001 Datalab Concepts.mp4 | 9.4 MB | ||
| 001 Dataprep Overview.mp4 | 25.1 MB | ||
| 001 Dataproc Overview.mp4 | 8.9 MB | ||
| 001 Deep Learning with TensorFlow.mp4 | 17 MB | ||
| 001 GCP Solutions Big Data.txt | 0 B | ||
| 001 Google AI and machine learning products.txt | 0 B | ||
| 001 Interacting with BigQuery.txt | 102.4 B | ||
| 001 Introduction to AutoML.mp4 | 10 MB | ||
| 001 Introduction to Data Storage in GCP.mp4 | 59.1 MB | ||
| 001 Introduction to Operationalizing ML Models.mp4 | 11.3 MB | ||
| 001 Keras overview.txt | 0 B | ||
| 001 Keras.txt | 0 B | ||
| 001 Machine Learning Introduction.mp4 | 25.6 MB | ||
| 001 MapReduce research paper.pdf | 186.2 KB | ||
| 001 MapReduce.mp4 | 49 MB | ||
| 001 PubSub Concepts.mp4 | 51.3 MB | ||
| 001 Reference Architectures Big Data.mp4 | 23.3 MB | ||
| 001 Reporting and Business Intelligence.mp4 | 7.8 MB | ||
| 001 Security and Regulation Overview.mp4 | 20.6 MB | ||
| 001 TensforFlow overview.txt | 0 B | ||
| 001 The difference between AI ML and deep learning.txt | 102.4 B | ||
| 001 Welcome.mp4 | 30.2 MB | ||
| 002 About This Course.mp4 | 48.4 MB | ||
| 002 Activation functions.txt | 102.4 B | ||
| 002 BigQuery Capacitor.txt | 102.4 B | ||
| 002 BigQuery Transfer Service.txt | 102.4 B | ||
| 002 BigQuery documentation - BigQuery jobs.txt | 102.4 B | ||
| 002 BigQuery documentation - loading data into BigQuery.txt | 102.4 B | ||
| 002 BigQuery documentation - table schemas.txt | 0 B | ||
| 002 BigQuery documentation - views.txt | 0 B | ||
| 002 BigQuery documentation - working with external data.txt | 102.4 B | ||
| 002 BigQuery documentation - working with tables.txt | 102.4 B | ||
| 002 Bigtable Application Profiles.txt | 102.4 B | ||
| 002 Bigtable Architecture.mp4 | 15.2 MB | ||
| 002 Bigtable IAM Roles.txt | 102.4 B | ||
| 002 Bigtable Quotas Limits.txt | 0 B | ||
| 002 Cloud Composer Architecture.mp4 | 8.9 MB | ||
| 002 Data Distributions.mp4 | 20.8 MB | ||
| 002 Data Processing Pipelines.mp4 | 18.8 MB | ||
| 002 Dataproc Basics.mp4 | 8.3 MB | ||
| 002 GCP Solutions AI ML.txt | 0 B | ||
| 002 Hadoop HDFS.mp4 | 22.8 MB | ||
| 002 IAM Best Practices.mp4 | 14.8 MB | ||
| 002 Introduction to Artificial Neural Networks.mp4 | 45.5 MB | ||
| 002 Kubeflow.mp4 | 7.9 MB | ||
| 002 L1 Regularisation.txt | 102.4 B | ||
| 002 L2 Regularisation.txt | 102.4 B | ||
| 002 LAB Working with Cloud Datalab.mp4 | 37.1 MB | ||
| 002 LAB Working with Cloud Dataprep.mp4 | 60 MB | ||
| 002 Learn Tensorflow.txt | 0 B | ||
| 002 Linear regression.txt | 102.4 B | ||
| 002 ML Terminology.txt | 102.4 B | ||
| 002 Machine Learning Basics.mp4 | 39.9 MB | ||
| 002 Mock data files.Mock data files | 97.8 KB | ||
| 002 Overview of deep learning.txt | 102.4 B | ||
| 002 Pipeline Lifecycle.mp4 | 16.1 MB | ||
| 002 PubSub Basics.mp4 | 8.9 MB | ||
| 002 Reference Architectures Artificial Intelligence and Machine Learning.mp4 | 10.8 MB | ||
| 002 Regularisation.txt | 102.4 B | ||
| 002 Sight with AutoML.mp4 | 12.5 MB | ||
| 002 Training models.txt | 102.4 B | ||
| 002 Using BigQuery.mp4 | 37.4 MB | ||
| 002 Vision.mp4 | 26.4 MB | ||
| 002 Weights and layers.txt | 102.4 B | ||
| 002 Worked gradient descent example.html | 38.5 KB | ||
| 002 Working with Data.mp4 | 16.2 MB | ||
| 003 AI Platform.mp4 | 9.1 MB | ||
| 003 Apache Pig.mp4 | 7.4 MB | ||
| 003 BigQuery documentation - working with clustered tables.txt | 102.4 B | ||
| 003 BigQuery documentation - working with partitions.txt | 102.4 B | ||
| 003 Bigtable Data Model.mp4 | 10.2 MB | ||
| 003 Bigtable Garbage Collection Defaults.txt | 102.4 B | ||
| 003 Cloud Storage.mp4 | 23.1 MB | ||
| 003 Course Audience and Prerequisites.mp4 | 12.3 MB | ||
| 003 Data Security.mp4 | 11.8 MB | ||
| 003 Dataflow Pipeline Concepts.mp4 | 15.2 MB | ||
| 003 Difference between supervised unsupervised and reinforcement learning.txt | 102.4 B | ||
| 003 Estimating Pi using the Monte Carlo method.txt | 102.4 B | ||
| 003 GCP Regions and Zones.txt | 102.4 B | ||
| 003 GCP Solutions IoT.txt | 102.4 B | ||
| 003 GCS Documentation.txt | 0 B | ||
| 003 GCS Pricing.txt | 0 B | ||
| 003 Introduction to Data Studio.mp4 | 7.7 MB | ||
| 003 Introduction to Jupyter Notebooks (ACG Course).txt | 102.4 B | ||
| 003 Introduction to clustering.txt | 102.4 B | ||
| 003 Introduction to linear regression.txt | 102.4 B | ||
| 003 Introduction to logistic regression.txt | 102.4 B | ||
| 003 Introduction to transfer learning.txt | 102.4 B | ||
| 003 LAB Jupyter Notebooks in GCP.mp4 | 40.2 MB | ||
| 003 LAB Working with Cloud Dataproc.mp4 | 21 MB | ||
| 003 LAB Working with Cloud PubSub.mp4 | 31.7 MB | ||
| 003 Lab Working with Cloud Composer.mp4 | 46.6 MB | ||
| 003 Language with AutoML.mp4 | 11.7 MB | ||
| 003 Machine Learning Types and Models.mp4 | 24.9 MB | ||
| 003 Monte Carlo method.txt | 0 B | ||
| 003 Neural Network Architectures.mp4 | 20.1 MB | ||
| 003 Partitioning and Clustering.mp4 | 23.6 MB | ||
| 003 Reference Architectures Internet of Things.mp4 | 11.2 MB | ||
| 003 Security Command Center Quick Start.txt | 102.4 B | ||
| 003 Submitting jobs to Cloud Dataproc.txt | 102.4 B | ||
| 003 Video Intelligence.mp4 | 17.8 MB | ||
| 003 War Peace at Project Gutenburg.txt | 0 B | ||
| 003 hadoop-wordcount.py.zip | 1.2 KB | ||
| 004 Advanced Cloud Composer.mp4 | 9.5 MB | ||
| 004 Advanced Dataflow Concepts.mp4 | 15.2 MB | ||
| 004 Advanced Dataproc.mp4 | 15.8 MB | ||
| 004 Agones Overview.txt | 0 B | ||
| 004 Airflow Plugins.html | 113.7 KB | ||
| 004 Apache Spark.mp4 | 30.2 MB | ||
| 004 Autoscaling Clusters.txt | 102.4 B | ||
| 004 Best Practices.mp4 | 21.6 MB | ||
| 004 Blocked Configurations.txt | 102.4 B | ||
| 004 Building a Neural Network.mp4 | 10.7 MB | ||
| 004 Charts and Filters.mp4 | 14 MB | ||
| 004 Cloud Bigtable examples.txt | 102.4 B | ||
| 004 Cloud DLP Pricing.txt | 0 B | ||
| 004 Concepts.txt | 102.4 B | ||
| 004 Controlling costs.txt | 102.4 B | ||
| 004 Cross validation.txt | 102.4 B | ||
| 004 Data Privacy.mp4 | 12.8 MB | ||
| 004 Dataproc Cluster Properties.txt | 102.4 B | ||
| 004 Dataproc IAM.txt | 102.4 B | ||
| 004 Early stopping.txt | 102.4 B | ||
| 004 GCP Samples (C).txt | 102.4 B | ||
| 004 GCP Samples (Go).txt | 102.4 B | ||
| 004 GCP Samples (Java).txt | 102.4 B | ||
| 004 GCP Samples (PHP).txt | 102.4 B | ||
| 004 GCP Samples (Python).txt | 102.4 B | ||
| 004 GCP Samples (Ruby).txt | 102.4 B | ||
| 004 GCP Solutions Gaming.txt | 0 B | ||
| 004 GCS Access Control Lists (ACLs).txt | 102.4 B | ||
| 004 GCS IAM Permissions.txt | 102.4 B | ||
| 004 L1 Regularisation.txt | 102.4 B | ||
| 004 L2 Regularisation.txt | 102.4 B | ||
| 004 LAB Cloud PubSub Client Libraries.mp4 | 40.6 MB | ||
| 004 LAB Working with Cloud Bigtable.mp4 | 51.8 MB | ||
| 004 Lab commands.Lab commands | 1.1 KB | ||
| 004 Language.mp4 | 25.1 MB | ||
| 004 Node.txt | 0 B | ||
| 004 Optimising storage.txt | 102.4 B | ||
| 004 Overfitting.mp4 | 21.2 MB | ||
| 004 Query performance.txt | 102.4 B | ||
| 004 Reference Architectures Mobile Gaming.mp4 | 13.2 MB | ||
| 004 Regularisation.txt | 102.4 B | ||
| 004 Service Accounts.mp4 | 14.9 MB | ||
| 004 Structured Data with AutoML.mp4 | 9.7 MB | ||
| 004 bored.py | 1 KB | ||
| 004 cbt Reference.txt | 102.4 B | ||
| 005 Advanced PubSub.mp4 | 17.3 MB | ||
| 005 Apache Kafka.mp4 | 17.1 MB | ||
| 005 Applied Machine Learning with BigQuery (ACG).txt | 102.4 B | ||
| 005 AutoML Vision API Tutorial.txt | 102.4 B | ||
| 005 BigQuery Data Transfer Service.txt | 0 B | ||
| 005 Bigtable Schema Design.mp4 | 16.6 MB | ||
| 005 Cloud KMS keys.txt | 102.4 B | ||
| 005 Cloud Storage Transfer Service.txt | 0 B | ||
| 005 Complying with COPPA FAQ.txt | 102.4 B | ||
| 005 Conversation.mp4 | 27.5 MB | ||
| 005 Data Loss Prevention and BigQuery.txt | 102.4 B | ||
| 005 Data Transfer Services.mp4 | 8.9 MB | ||
| 005 Dataflow Security and Access.mp4 | 17.1 MB | ||
| 005 EU Data Protection Rules (GDPR).txt | 102.4 B | ||
| 005 Encryption at rest.txt | 102.4 B | ||
| 005 External Resources and Tutorials.mp4 | 8.7 MB | ||
| 005 FedRAMP FAQs.txt | 0 B | ||
| 005 GCP Compliance Resource Center.txt | 0 B | ||
| 005 Hyperparameter tuning.txt | 102.4 B | ||
| 005 Hyperparameters and parameters.txt | 102.4 B | ||
| 005 Hyperparameters.mp4 | 10 MB | ||
| 005 Industry Regulation.mp4 | 17.2 MB | ||
| 005 Introduction to Jupyter Notebooks (ACG).txt | 102.4 B | ||
| 005 LAB Cloud Dataproc with the GCS Connector.mp4 | 25 MB | ||
| 005 ML Basics with Keras Tutorials.txt | 102.4 B | ||
| 005 PCI DSS Quick Reference Guide.txt | 102.4 B | ||
| 005 Predefined roles and permissions.txt | 102.4 B | ||
| 005 Primitive roles and permissions.txt | 102.4 B | ||
| 005 Project Gutenberg.txt | 0 B | ||
| 005 PubSub IAM Roles.txt | 102.4 B | ||
| 005 PubSub Stackdriver Metrics.txt | 102.4 B | ||
| 005 Python for Beginners (ACG).txt | 0 B | ||
| 005 Securing BigQuery.mp4 | 11.6 MB | ||
| 005 TensorFlow 2 Quickstart Tutorial.txt | 102.4 B | ||
| 005 Visualizing Cloud Bigtable Access Patterns at Twitter for Optimizing Analytics (YouTube).txt | 0 B | ||
| 005 Visualizing GCP Billing using BigQuery and Data Studio.txt | 102.4 B | ||
| 005 wordcount.py | 1 KB | ||
| 006 Audit logs.txt | 102.4 B | ||
| 006 BigQuery Monitoring and Logging.mp4 | 9.1 MB | ||
| 006 Bigtable Advanced Concepts.mp4 | 14.3 MB | ||
| 006 Bleeding hand picture.txt | 102.4 B | ||
| 006 Cleaning data.txt | 102.4 B | ||
| 006 Cloud SQL Documentation.txt | 0 B | ||
| 006 Cloud SQL.mp4 | 22.6 MB | ||
| 006 Cute dog picture.txt | 102.4 B | ||
| 006 Deploying a pipeline.txt | 102.4 B | ||
| 006 Exam Guide Breakdown.mp4 | 60.3 MB | ||
| 006 Exam Tips.mp4 | 8.6 MB | ||
| 006 Feature Engineering.mp4 | 23.6 MB | ||
| 006 Feature engineering.txt | 102.4 B | ||
| 006 GCP Pricing.txt | 0 B | ||
| 006 LAB Loosely Coupled Services with Cloud PubSub.mp4 | 35.8 MB | ||
| 006 LAB Working with Cloud ML APIs.mp4 | 52.6 MB | ||
| 006 Lab code.Lab code | 3.4 KB | ||
| 006 Monitoring a Cloud Bigtable Instance.txt | 102.4 B | ||
| 006 Monitoring using Stackdriver.txt | 0 B | ||
| 006 Replicating from an external server.txt | 102.4 B | ||
| 006 Requirements and tips for configuring replication.txt | 102.4 B | ||
| 006 Source Code gen_thumbnail.Source Code gen_thumbnail | 2.3 KB | ||
| 006 Using Dataflow.mp4 | 22.1 MB | ||
| 007 BigQuery ML documentation.txt | 0 B | ||
| 007 Cloud Bigtable examples.txt | 102.4 B | ||
| 007 Exam Tips.mp4 | 10.4 MB | ||
| 007 Fire Weather Index (FWI) System.txt | 102.4 B | ||
| 007 Forest Fires dataset.txt | 102.4 B | ||
| 007 LAB Creating a Cloud SQL Instance and Loading Data.mp4 | 29.5 MB | ||
| 007 LAB Loading and Querying Data with Cloud Bigtable.mp4 | 40.7 MB | ||
| 007 LAB Stream Data through Cloud PubSub to BigQuery.mp4 | 59.6 MB | ||
| 007 MOCK_DATA.csv | 39.2 KB | ||
| 007 Machine Learning with BigQuery ML.mp4 | 10.4 MB | ||
| 007 What to Expect From the Exam.mp4 | 24.5 MB | ||
| 007 dataloader.py | 921.6 B | ||
| 007 forestfires.csv | 7.7 KB | ||
| 007 forumdb.sql | 65.5 KB | ||
| 007 transactions.py | 1.1 KB | ||
| 008 Cloud Firestore Documentation.txt | 0 B | ||
| 008 Cloud Firestore.mp4 | 23.6 MB | ||
| 008 Exam Tips.mp4 | 9.2 MB | ||
| 008 LAB Working with Cloud Dataflow.mp4 | 31.6 MB | ||
| 008 Lab Commands.Lab Commands | 614.4 B | ||
| 008 Thank You and Good Luck.mp4 | 10.2 MB | ||
| 009 ANSI SQL best practices.txt | 102.4 B | ||
| 009 Beam Programming Guide.txt | 102.4 B | ||
| 009 CAP Theorem.txt | 0 B | ||
| 009 Cloud Spanner Documentation.txt | 0 B | ||
| 009 Cloud Spanner.mp4 | 28.3 MB | ||
| 009 Distributed database quorums.txt | 102.4 B | ||
| 009 Dummy data files.Dummy data files | 83.3 KB | ||
| 009 LAB Streaming Pipelines with Cloud Dataflow.mp4 | 60 MB | ||
| 009 LAB Working with BigQuery.mp4 | 38.6 MB | ||
| 009 Lab Code.Lab Code | 3.1 KB | ||
| 009 Lab Commands.Lab Commands | 409.6 B | ||
| 009 Loading CSV data from Cloud Storage.txt | 102.4 B | ||
| 009 Loading JSON data from Cloud Storage.txt | 102.4 B | ||
| 009 Multi-regional best practices.txt | 102.4 B | ||
| 009 Regional best practices.txt | 102.4 B | ||
| 010 GCP Samples (C).txt | 102.4 B | ||
| 010 GCP Samples (Go).txt | 102.4 B | ||
| 010 GCP Samples (Java).txt | 102.4 B | ||
| 010 GCP Samples (PHP).txt | 102.4 B | ||
| 010 GCP Samples (Python).txt | 102.4 B | ||
| 010 GCP Samples (Ruby).txt | 102.4 B | ||
| 010 LAB Advanced BigQuery Features.mp4 | 58.1 MB | ||
| 010 LAB Working with Cloud Spanner.mp4 | 21.8 MB | ||
| 010 Lab Commands.Lab Commands | 1.9 KB | ||
| 010 Node.txt | 0 B | ||
| 010 spannerlab-schema.sql | 307.2 B | ||
| 011 Cloud Memorystore Documentation.txt | 0 B | ||
| 011 Cloud Memorystore.mp4 | 10.4 MB | ||
| 012 LAB Working with Cloud Memorystore.mp4 | 36 MB | ||
| 012 Redis-CLI Documentation.txt | 0 B | ||
| 012 Retwis GitHub repo.txt | 0 B | ||
| 013 Comparing Storage Options.mp4 | 14.7 MB | ||
| 014 Exam Tips.mp4 | 6.9 MB | ||
| 1. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url | 307.2 B | ||
| 2. (NulledPremium.com) Download E-Learning, E-Books, Audio-Books, & more.etc.url | 204.8 B | ||
| 3. (FTUApps.com) Download Cracked Developers Applications For Free.url | 204.8 B | ||
| How you can help our Group!.txt | 204.8 B | ||
| ▲ 283 total files | |||
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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