Google Cloud Professional Data Engineer Certification Training - CloudThat - Training

Course Overview

Professional Data Engineers enable data-driven decision making by collecting, transforming, and publishing data. A Data Engineer should be able to design, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance; scalability and efficiency; reliability and fidelity; and flexibility and portability. A Data Engineer should also be able to leverage, deploy, and continuously train pre-existing machine learning models.

 

After completing this course, students will be able to:

  • Acquire knowledge on cloud computing basics and how Google Cloud products and services can be used to achieve an organization’s goals.
  • Attain skills required to clear the GCP Cloud Digital Leader Certification Exam.

Upcoming Batches

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Key Features

  • Our Google Cloud Professional Data Engineer training modules have 50% - 60% hands-on lab sessions to encourage Thinking-Based Learning (TBL).
  • Interactive-rich virtual and face-to-face classroom teaching to inculcate Problem-Based Learning (PBL).
  • Industry certified instructor-led training and mentoring sessions to develop Competency-Based Learning (CBL).
  • Well-structured use-cases to simulate challenges encountered in a Real-World environment.
  • Integrated teaching assistance and support through experts designed Learning Management System (LMS) and ExamReady platform.
  • Being an authorized GCP Learning Partner gives us the edge over competition.

Who Should Attend

  • This Google Data Engineer certification course is for Data Scientists, DevOps Engineers, Solution Architects, and anyone willing to learn about data engineering and machine learning in the context of the Google Cloud Platform.

Prerequisites

  • Google Cloud Associate Engineer certification.
  • Course Outline Download Course Outline

    • Designing Data Processing Systems
    • Building and Operationalizing Data Processing Systems
    • Operationalizing Machine Learning Models
    • Security, Policy, and Reliability

    • Introduction
    • Big Data and Machine Learning on Google Cloud
    • Data Engineering for Streaming Data
    • Big Data with BigQuery
    • Machine Learning Options on Google Cloud
    • The Machine Learning Workflow with Vertex AI

    Hands-On

    • Vertex AI: Qwik Start
    • Exploring a BigQuery Public Dataset
    • Vertex AI: Predicting Loan Risk with AutoML

    • Introduction
    • Introduction to Data Engineering
    • Building a Data Lake
    • Building a Data Warehouse

    Hands-On

    • BigQuery: Qwik Start - Command Line
    • Creating a Data Warehouse Through Joins and Unions
    • Build and Execute MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors

    • Introduction to Building Batch Data Pipelines
    • Executing Spark on Dataproc
    • Serverless Data Processing with Dataflow
    • Manage Data Pipelines with Cloud Data Fusion and Cloud Composer

    Hands-On

    • Dataflow: Qwik Start - Templates
    • Dataflow: Qwik Start - Python
    • Dataproc: Qwik Start - Console
    • Cloud Composer: Copying BigQuery Tables Across Different Locations

    • Introduction to Processing Streaming Data
    • Serverless Messaging with Pub/Sub
    • Dataflow Streaming Features
    • High-Throughput BigQuery and Bigtable Streaming Features
    • Advanced BigQuery Functionality and Performance

    Hands-On

    • Building an IoT Analytics Pipeline on Google Cloud
    • ETL Processing on Google Cloud Using Dataflow and BigQuery
    • Creating Date-Partitioned Tables in BigQuery
    • Troubleshooting and Solving Data Join Pitfalls
    • Working with JSON, Arrays, and Structs in BigQuery

    • Introduction to Analytics and AI
    • Prebuilt ML Model APIs for Unstructured Data
    • Big Data Analytics with Notebooks
    • Production ML Pipelines with Kubeflow
    • Custom Model building with SQL in BigQuery ML
    • Custom Model Building with AutoML

    Hands-On

    • Dataprep: Qwik Start
    • Creating a Data Transformation Pipeline with Cloud Dataprep
    • Predict Visitor Purchases with a Classification Model in BQML
    • Cloud Natural Language API: Qwik Start
    • Google Cloud Speech API: Qwik Start
    • Video Intelligence: Qwik Start

    Certification

    • By earning GCP Data Engineer certification, you can be competent Google certified professional.
    • Demonstrate skills and knowledge to build, monitor, and tune high performance data engineering systems.
    • On successful completion of Google Data Engineer course, aspirants receive a Course Completion Certificate from us.
    • By successfully clearing the Google Data Engineer exam, aspirants earn Google Certification.

    Course Fee

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    Course ID: 11542

    Course Price at

    ₹ 44900 + 18% GST

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