Google Data Engineer - Professional Training

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Google Data Engineer - Professional Certification Training is designed for data professionals and individuals preparing for the Google Professional Data Engineer exam. We, at Multisoft Systems, are engaged in providing this course with certified subject matter experts as per industry defined standards.

Google Data Engineer - Professional Training is designed to help data professionals and individuals prepare for the Google Professional Data Engineer exam. It is going to be a great option for you if you want to gain a solid understanding of the various data processing components of the Google Cloud Platform. You can go for this course if you have a basic knowledge of database management. We, at Multisoft Systems, are offering the course with certified industry experts.

You will learn the techniques of building data structures and databases, designing data processing systems, analyzing data and enabling machine learning, maintaining data structures and databases, visualizing data and designing secure data processing systems, and ensuring the reliability of data processing infrastructure. To go for this certification exam, you need at least 3 years of industry experience in designing and managing solutions with the use of Google Cloud.

Google Data Engineer Professional Course Objective
  • How to design a data processing system?
  • How to build data structures and databases?
  • How to maintain data structures and databases?
  • How to analyze data and enable machine learning?
  • How to optimize data representations, data infrastructure performance, and cost?
  • How to visualize data and design secure data processing systems?
  • How to ensure the reliability of data processing infrastructure?
Google Data Engineer Professional Online Training
  • Recorded Videos After Training
  • Digital Learning Material
  • Course Completion Certificate
  • 24x7 After Training Support
Target Audience
  • Data professionals
  • Individuals preparing for the Google Professional Data Engineer exam
Google Data Engineer Professional Course Prerequisites
  • Basic database knowledge
Google Data Engineer Professional Course Certification
  • Multisoft Systems will provide you with a training completion certificate after completing this Google Data Engineer Professional Certification Training.

Google Data Engineer - Professional Certification Training is designed for data professionals and individuals preparing for the Google Professional Data Engineer exam. We, at Multisoft Systems, are engaged in providing this course with certified subject matter experts as per industry defined standards.

Google Data Engineer - Professional Training is designed to help data professionals and individuals prepare for the Google Professional Data Engineer exam. It is going to be a great option for you if you want to gain a solid understanding of the various data processing components of the Google Cloud Platform. You can go for this course if you have a basic knowledge of database management. We, at Multisoft Systems, are offering the course with certified industry experts.

You will learn the techniques of building data structures and databases, designing data processing systems, analyzing data and enabling machine learning, maintaining data structures and databases, visualizing data and designing secure data processing systems, and ensuring the reliability of data processing infrastructure. To go for this certification exam, you need at least 3 years of industry experience in designing and managing solutions with the use of Google Cloud.

Google Data Engineer Professional Course Objective
  • How to design a data processing system?
  • How to build data structures and databases?
  • How to maintain data structures and databases?
  • How to analyze data and enable machine learning?
  • How to optimize data representations, data infrastructure performance, and cost?
  • How to visualize data and design secure data processing systems?
  • How to ensure the reliability of data processing infrastructure?
Google Data Engineer Professional Online Training
  • Recorded Videos After Training
  • Digital Learning Material
  • Course Completion Certificate
  • 24x7 After Training Support
Target Audience
  • Data professionals
  • Individuals preparing for the Google Professional Data Engineer exam
Google Data Engineer Professional Course Prerequisites
  • Basic database knowledge
Google Data Engineer Professional Course Certification
  • Multisoft Systems will provide you with a training completion certificate after completing this Google Data Engineer Professional Certification Training.

Google Data Engineer - Professional Training Course Content

Module 1: Introduction

  • About This Course
  • Course Audience and Prerequisites
  • A Note About Demo Lessons

Module 2: Data Processing Fundamentals

  • Data Processing Concepts
  • Data Processing Pipelines

Module 3: Storage and Databases

  • Introduction to Data Storage in GCP
  • Working with Data
  • Cloud Storage
  • Service Accounts
  • Data Transfer Services
  • Cloud SQL
  • Demo: Creating a Cloud SQL Instance and Loading Data
  • Managing Google Cloud SQL Instances
  • Hands-On Lab
  • Working with Data in Google Cloud SQL
  • Hands-On Lab
  • Cloud Firestore
  • Exploring Cloud Firestore in Datastore Mode
  • Hands-On Lab
  • Cloud Run Data in GCS and Firestore
  • Hands-On Lab
  • Cloud Spanner
  • Demo: Working with Cloud Spanner
  • Setting Up for Google Cloud Spanner
  • Hands-On Lab
  • Cloud Memorystore
  • Demo: Working with Cloud Memorystore
  • Comparing Storage Options
  • Exam Tips

Module 4: Big Data Ecosystem

  • MapReduce
  • Hadoop & HDFS
  • Apache Pig
  • Apache Spark
  • Apache Kafka

Module 5: Real-Time Messaging with Pub/Sub

  • Pub/Sub Concepts
  • Pub/Sub Basics
  • Demo: Working with Cloud Pub/Sub
  • Demo: Cloud Pub/Sub Client Libraries
  • Advanced Pub/Sub
  • Demo: Loosely Coupled Services with Cloud Pub/Sub
  • Demo: Stream Data through Cloud Pub/Sub to BigQuery
  • Exam Tips 

Module 6: Pipelines with Cloud Dataflow

  • Dataflow Introduction
  • Pipeline Lifecycle
  • Dataflow Pipeline Concepts
  • Advanced Dataflow Concepts
  • Dataflow Security and Access
  • Using Dataflow
  • Exam Tips
  • Demo: Working with Cloud Dataflow
  • Demo: Streaming Pipelines with Cloud Dataflow
  • Create Streaming Data Pipeline on GCP with Cloud Pub/Sub, Dataflow, and BigQuery

Module 7: Managed Spark with Cloud Dataproc

  • Dataproc Overview
  • Dataproc Basics
  • Demo: Working with Cloud Dataproc
  • Advanced Dataproc
  • Demo: Cloud Dataproc with the GCS Connector
  • Exam Tips

Module 8: NoSQL Data with Cloud Bigtable

  • Bigtable Concepts
  • Bigtable Architecture
  • Bigtable Data Model
  • Demo: Working with Cloud Bigtable
  • Bigtable Schema Design
  • Bigtable Advanced Concepts
  • Demo: Loading and Querying Data with Cloud Bigtable
  • Exam Tips

Module 9: Data Analytics with BigQuery

  • BigQuery Basics
  • Using BigQuery
  • Partitioning and Clustering
  • Best Practices
  • Securing BigQuery
  • BigQuery Monitoring and Logging
  • Machine Learning with BigQuery ML
  • Exam Tips
  • Demo: Working with BigQuery
  • Demo: Advanced BigQuery Features

Module 10: Exploration with Cloud Datalab

  • Datalab Concepts
  • Demo: Working with Cloud Datalab
  • Demo: Jupyter Notebooks in GCP

Module 11: Visualization with Cloud Data Studio

  • Reporting and Business Intelligence
  • Data Distributions
  • Introduction to Data Studio
  • Charts and Filters

Module 12: Composer

  • Cloud Composer Overview
  • Cloud Composer Architecture
  • Demo: Working with Cloud Composer
  • Advanced Cloud Composer

Module 13: Introduction to Machine Learning

  • Machine Learning Introduction
  • Machine Learning Basics
  • Machine Learning Types and Models
  • Overfitting
  • Hyperparameters
  • Feature Engineering

Module 14: Machine Learning with TensorFlow

  • Deep Learning with TensorFlow
  • Introduction to Artificial Neural Networks
  • Neural Network Architectures
  • Building a Neural Network

Module 15: Using Pre-Trained ML Cloud APIs

  • Cloud AI Cloud APIs
  • Vision
  • Video Intelligence
  • Language
  • Conversation
  • Demo: Working with Cloud ML APIs

Module 16: Leveraging Auto ML Platform

  • Introduction to AutoML
  • Sight with AutoML
  • Language with AutoML
  • Structured Data with AutoML

Module 17: Operationalizing Machine Learning Models

  • Introduction to Operationalizing ML Models
  • Kubeflow
  • AI Platform

Module 18: Data Security and Industry Regulation

  • Security and Regulation Overview
  • IAM Best Practices
  • Data Security
  • Data Privacy
  • Industry Regulation

Module 19: Dataprep

  • Dataprep Overview
  • Demo: Working with Cloud Dataprep

Module 20: Preparing for the Professional Data Engineer Exam

  • Reference Architectures: Big Data
  • Reference Architectures: Artificial Intelligence and Machine Learning
  • Reference Architectures: Internet of Things
  • Reference Architectures: Mobile & Gaming
  • External Resources and Tutorials
  • Exam Guide Breakdown
  • What to Expect From the Exam
  • Thank You and Good Luck!
  • Keep Up to Date with GCP This Month
     

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