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The Data Engineer certification focuses on designing and managing data infrastructure, including data pipelines, storage solutions, and data processing frameworks. It equips professionals with skills to handle large-scale data systems, optimize data workflows, and ensure efficient data management. Ideal for those looking to advance their expertise in data engineering and analytics.

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( 4.2 Ratings )

Live Online Classes starting on 01 January, 1970

Data Engineer

Professional Data Engineer Certification Overview

This four-day instructor-led course offers a comprehensive hands-on introduction to designing and building data processing systems on the Google Cloud Platform (GCP). Participants will engage in a combination of presentations, demos, and labs to learn how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning solutions. The course covers handling structured, unstructured, and streaming data effectively.

 

Audience: This course is ideal for experienced developers responsible for managing big data transformations, including:

  • Extracting, loading, transforming, cleaning, and validating data

  • Designing data processing pipelines and architectures

  • Creating and maintaining machine learning and statistical models

  • Querying datasets, visualizing results, and generating reports

 

Prerequisites: To maximize learning, participants should have:

  • Completed the Google Cloud Fundamentals: Core Infrastructure (GCPFCI) course or have equivalent experience

  • Basic proficiency in SQL or a similar query language

  • Experience in data modeling and ETL (Extract, Transform, Load) activities

  • Experience developing applications using a common programming language such as Python

  • Familiarity with basic statistics and machine learning concepts

 

Learning Outcomes: By the end of this course, participants will be able to:

  • Design and build data processing systems on Google Cloud Platform

  • Leverage unstructured data using Spark and ML APIs on Cloud Dataproc

  • Process batch and streaming data with autoscaling pipelines on Cloud Dataflow

  • Derive insights from large datasets using Google BigQuery

  • Train, evaluate, and deploy machine learning models with TensorFlow and Cloud ML

  • Generate instant insights from streaming data

(4.2 Ratings)

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