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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

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

Learning Outcomes

  • 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

Course Outline

Day 1: Serverless Data Analysis

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

Day 2: Leveraging unstructured data

  • 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

  • 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

  • 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

GCP Learning Paths

Want to boost your career in GCP? Click on the roles below to see QA‘s learning pathways, specially designed to give you the skills to succeed.

= Required
= Certification
Data Scientist
Data Engineer
Developer Software Development Experience
Architect Enterprise Architecture Experience
Administrator Windows Administrator Experience
Data Engineer Average salary: £70,000*

Total individual course price: £7,996 ex VAT

Bundle price: £6,505 ex VAT

Saving: £1,491

10 days

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Administrator Average salary: £51,250*

Total individual course price: £3,840 ex VAT

Bundle price: £3,090 ex VAT

Saving: £750

5 days

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Key for bundle contents
= Exam Preparation
= Exam
= Practice Exam
= Exam Voucher
= Tutor Support
= Pre Course Work
*This is based on QA research

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