Data Engineering on Google Cloud Platform

4 Day Course
Hands On
Official Curriculum
Code GCPDEGP

Book Now - 3 Delivery Methods Available:

Classroom Virtual Classroom Private Group - Virtual Self-Paced Online

Overview

This four-day instructor-led class provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform.

This class is intended for experienced developers who are responsible for managing big data transformations including:

  • Extracting, Loading, Transforming, cleaning, and validating data
  • Designing pipelines and architectures for data processing
  • Creating and maintaining machine learning and statistical models
  • Querying datasets, visualizing query results and creating reports

Objectives

  • Design and build data processing systems on Google Cloud Platform
  • Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow
  • Derive business insights from extremely large datasets using Google BigQuery
  • Train, evaluate and predict using machine learning models using Tensorflow and Cloud ML
  • Leverage unstructured data using Spark and ML APIs on Cloud Dataproc
  • Enable instant insights from streaming data

Training Partners

We work with the following best of breed training partners using our bulk buying power to bring you a wider range of dates, locations and prices.

Modules

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Day 1: Serverless Data Analysis (2 topics)

  • Module 1: Serverless data analysis with BigQuery
  • Module 2: Serverless, autoscaling data pipelines with Dataflow

Day 2: Leveraging unstructured data (4 topics)

  • Module 3: Google Cloud Dataproc Overview
  • Module 4: Running Dataproc Jobs
  • Module 5: Integrating Dataproc with Google Cloud Platform
  • Module 6: Making Sense of Unstructured Data with Google's Machine Learning APIs

Day 3: Serverless Machine Learning (5 topics)

  • Module 7: Getting started with Machine Learning
  • Module 8: Building ML models with Tensorflow
  • Module 9: Scaling ML models with CloudML
  • Module 10: Feature Engineering
  • Module 11: ML architectures

Day 4: Resilient streaming systems (6 topics)

  • Module 12: Need for real-time streaming analytics
  • Module 13: Architecture of streaming pipelines
  • Module 14: Stream data and events into PubSub
  • Module 15: Build a stream processing pipeline
  • Module 16: High throughput and low-latency with Bigtable
  • Module 17: Building Dashboards

Prerequisites

To get the most of out of this course, participants should have:

  • Completed Google Cloud Fundamentals: Big Data & Machine Learning OR have equivalent experience
  • Basic proficiency with common query language such as SQL
  • Experience with data modeling, extract, transform, load activities
  • Developing applications using a common programming language such Python
  • Familiarity with Machine Learning and/or statistics

Relevant Certifications

Scheduled Dates

Please select from the dates below to make an enquiry or booking.

Pricing

Different pricing structures are available including special offers. These include early bird, late availability, multi-place, corporate volume and self-funding rates. Please arrange a discussion with a training advisor to discover your most cost effective option.

Code Location Duration Price May Jun Jul Aug Sep Oct
GCPDEGP
Virtual Classroom (Virtual On-Line)
4 Days $3,955

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